This slide show talks about my Graduation Project which is pending this year.My Graduation project will be around "Planning,Learning and Adaptation in Real-time Strategy Games".The Presentation consists of 2 main parts, one about the techniques used in game AI engines ,and the other about the latest research in Real-Time Strategy Games concerning learning and planning.My partner in this Project is AbdelRahman Al- Ogail.
The document describes a library management system created by five students. The system allows users to add members and books, search for members and books, and borrow and return books. It has four main modules: inputting data, extracting data, generating reports, and search. The system aims to automate library processes and reduce errors. It uses PHP and MySQL for a user-friendly interface and fast access. The document outlines the system's objectives, technologies used, modules, and concludes that the goals of optimizing resources, simplifying operations, and having a user-friendly system were achieved.
This document discusses challenges in information assurance and authentication. It introduces common web authentication methods like SAML and Shibboleth that enable single sign-on across domains using federated identity. SAML allows sharing of authentication and authorization data in XML format. Shibboleth is an open source single sign-on system that uses SAML and allows identity federations. OpenID is also discussed as a decentralized authentication standard used by many websites. The document compares and contrasts these different authentication methods.
AI and ML Series - Introduction to Generative AI and LLMs - Session 1DianaGray10
Session 1
👉This first session will cover an introduction to Generative AI & harnessing the power of large language models. The following topics will be discussed:
Introduction to Generative AI & harnessing the power of large language models.
What’s generative AI & what’s LLM.
How are we using it in our document understanding & communication mining models?
How to develop a trustworthy and unbiased AI model using LLM & GenAI.
Personal Intelligent Assistant
Speakers:
📌George Roth - AI Evangelist at UiPath
📌Sharon Palawandram - Senior Machine Learning Consultant @ Ashling Partners & UiPath MVP
📌Russel Alfeche - Technology Leader RPA @qBotica & UiPath MVP
This document provides a summary of requirements for a Library Management System. It includes 3 sections:
1. Introduction - Defines the purpose, scope and intended audience of the system which is to manage library processes like book borrowing online.
2. Overall Description - Outlines key product functions for administrators and users, the operating environment, user characteristics and design constraints.
3. External Interfaces - Specifies the user interface requirements including login, search and categories. Hardware and software interfaces are also listed.
The document provides a high-level overview of the essential functions, behaviors and non-functional requirements for the library management software.
This document presents a project on an e-farming system. The project aims to help Indian farmers sell their agricultural products online and provide information to help improve farming practices. It will allow farmers to purchase supplies directly from sellers and sell crops without relying on agents or wholesalers. The system will provide online information about crops, tools and seeds. It will help farmers increase their income and living standards by marketing crops directly to consumers.
The document provides a software requirements specification for a rental property management system. It includes sections on introduction, overall description of the system, external interface requirements, key system features, and other non-functional requirements. The main system features include authentication, adding properties and photos, location search, property search, shortlisting properties, and adding advertisements. The system will be a web application built using Python, Django, PostgreSQL, and other frameworks.
With the increasingly connected world revolving around the revolution of internet and new technologies like mobiles, smartphones, and tablets, and with the wide usage of wireless technologies, the information security risks have increased. Both individuals and organizations are under regular attacks for commercial or non-commercial gains. The objectives of such attacks may be to take revenge, malign the reputation of a competitor organization, understand the strategies and sensitive information about the competitor, simply have fun of exploiting the vulnerabilities. Hence, the need to protect information assets and ensure information security receives adequate attention.
In this session, I will discuss how AI and Machine Learning can be applied in detecting, predicting and preventing cyber security/information security vulnerabilities and what are the benefits of using Machine Learning and AI. We also touch upon some of the tools available to perform the same.
The document describes a library management system created by five students. The system allows users to add members and books, search for members and books, and borrow and return books. It has four main modules: inputting data, extracting data, generating reports, and search. The system aims to automate library processes and reduce errors. It uses PHP and MySQL for a user-friendly interface and fast access. The document outlines the system's objectives, technologies used, modules, and concludes that the goals of optimizing resources, simplifying operations, and having a user-friendly system were achieved.
This document discusses challenges in information assurance and authentication. It introduces common web authentication methods like SAML and Shibboleth that enable single sign-on across domains using federated identity. SAML allows sharing of authentication and authorization data in XML format. Shibboleth is an open source single sign-on system that uses SAML and allows identity federations. OpenID is also discussed as a decentralized authentication standard used by many websites. The document compares and contrasts these different authentication methods.
AI and ML Series - Introduction to Generative AI and LLMs - Session 1DianaGray10
Session 1
👉This first session will cover an introduction to Generative AI & harnessing the power of large language models. The following topics will be discussed:
Introduction to Generative AI & harnessing the power of large language models.
What’s generative AI & what’s LLM.
How are we using it in our document understanding & communication mining models?
How to develop a trustworthy and unbiased AI model using LLM & GenAI.
Personal Intelligent Assistant
Speakers:
📌George Roth - AI Evangelist at UiPath
📌Sharon Palawandram - Senior Machine Learning Consultant @ Ashling Partners & UiPath MVP
📌Russel Alfeche - Technology Leader RPA @qBotica & UiPath MVP
This document provides a summary of requirements for a Library Management System. It includes 3 sections:
1. Introduction - Defines the purpose, scope and intended audience of the system which is to manage library processes like book borrowing online.
2. Overall Description - Outlines key product functions for administrators and users, the operating environment, user characteristics and design constraints.
3. External Interfaces - Specifies the user interface requirements including login, search and categories. Hardware and software interfaces are also listed.
The document provides a high-level overview of the essential functions, behaviors and non-functional requirements for the library management software.
This document presents a project on an e-farming system. The project aims to help Indian farmers sell their agricultural products online and provide information to help improve farming practices. It will allow farmers to purchase supplies directly from sellers and sell crops without relying on agents or wholesalers. The system will provide online information about crops, tools and seeds. It will help farmers increase their income and living standards by marketing crops directly to consumers.
The document provides a software requirements specification for a rental property management system. It includes sections on introduction, overall description of the system, external interface requirements, key system features, and other non-functional requirements. The main system features include authentication, adding properties and photos, location search, property search, shortlisting properties, and adding advertisements. The system will be a web application built using Python, Django, PostgreSQL, and other frameworks.
With the increasingly connected world revolving around the revolution of internet and new technologies like mobiles, smartphones, and tablets, and with the wide usage of wireless technologies, the information security risks have increased. Both individuals and organizations are under regular attacks for commercial or non-commercial gains. The objectives of such attacks may be to take revenge, malign the reputation of a competitor organization, understand the strategies and sensitive information about the competitor, simply have fun of exploiting the vulnerabilities. Hence, the need to protect information assets and ensure information security receives adequate attention.
In this session, I will discuss how AI and Machine Learning can be applied in detecting, predicting and preventing cyber security/information security vulnerabilities and what are the benefits of using Machine Learning and AI. We also touch upon some of the tools available to perform the same.
The document discusses analyzing the business case for IT systems projects. It explains that the systems planning phase involves reviewing proposals to determine if they present a strong business case. Analysts must consider the company's mission, objectives and IT needs. The process starts with a systems request and preliminary investigation to evaluate feasibility, fact finding, and reporting to management. Setting project priorities involves rejecting infeasible requests and prioritizing remaining items based on greatest benefit, lowest cost and shortest timeline.
The document is a summary of a student's hostel management system project. It includes acknowledgements, an abstract, table of contents, introduction, system analysis, design, implementation, testing, and conclusion sections. The introduction defines the problems with existing manual hostel management systems and the objectives of the proposed computerized system. The system analysis compares the existing and proposed systems. The proposed system aims to automate processes, provide quick access to accurate information, and reduce costs and errors compared to the manual system. The system design and implementation sections describe the hardware, software, database tables, user interfaces, and coding used to develop the project.
All Actors of the System
Subsystems of the system
Use case with all actors with all subsystem
Separate use case diagram of all subsystems with all actors
Separate table of all use case of all sub systems with actors
Define the action of actors and system response for all use case.
The document describes a graphics editor program that simulates the MS Paint application. It uses OpenGL for graphics rendering and GLUT for creating windows and rendering scenes. Key features implemented include tools for drawing shapes, images, and text. OpenGL functions are used for rendering while GLUT functions handle window creation and events. The design section covers header files, OpenGL/GLUT functions, and user-defined functions for tasks like drawing, erasing, and filling shapes. Implementation details are provided for various drawing algorithms and user interface elements.
Library mangement system project srs documentation.docjimmykhan
The document describes a library management system created in Java. It has four main modules: inserting data into the database, extracting data from the database, generating reports on borrowed and available books, and a search facility. The proposed system automates library processes like adding members and books, searching, borrowing and returning books. This makes transactions faster and reduces errors compared to the manual existing system. The system was implemented using Java, MS Access for the database, and designed to run on Windows operating systems. Testing was done to check functionality and ensure all requirements were met.
This file contains full report of online fitness gym.And it was prepare by Abhishek, Saurav and Jitendra. If any query please contact at abhishek96patel@gmail.com
General Meeting: "Opening a pandora's box"
Deepasri Dattaraghava and Annya Satyaviana on February 10, 2023
Join us for a thought-provoking meeting where we will all delve into the question of whether ChatGPT and other language models are doing more harm than good.
The event will feature keynote speakers, panel discussions, and interactive sessions that will explore the impact of AI on society, ethics, and the future of work.
Come ready to collaborate and discuss. Attendees will have the opportunity to engage with experts in AI and the broader university community to gain a deeper understanding of the potential dangers and benefits of advanced AI technologies.
Don't miss this opportunity to be part of the important conversation around the role of AI in our world.
This session was presented at the AWS Community Day in Munich (September 2023). It's for builders that heard the buzz about Generative AI but can’t quite grok it yet. Useful if you are eager to connect the dots on the Generative AI terminology and get a fast start for you to explore further and navigate the space. This session is largely product agnostic and meant to give you the fundamentals to get started.
The document provides details about a library management system project done by Sumedh Kumar Singh at MECON Limited, Ranchi under the guidance of Mr. P.K. Dubey. The project report includes sections on feasibility study, system architecture, database creation and tables, forms design, and deployment. The proposed system automates processes like book and member management, book issuing and returning, and calculates any fines. It aims to provide efficient services to users and reduce the workload for library staff.
The document discusses the importance of operating system (OS) security and the challenges involved. It notes that OSes control hardware access and scheduling, so flaws can compromise all security. Modern OSes are multi-user and multi-tasking, requiring protection of processes, memory, I/O devices, and more. Key OS security functions include memory protection, file protection, authentication, and authorization. Mechanisms like separation, access controls, and complete mediation are important to enforce security policies.
The document outlines the scope and design of a library management system. It includes sections on project purpose, scope, assumptions, functionality, specific requirements, tools/platform, resources used, design specification including entity relationship and data flow diagrams, database structure, module description, process logic, types of reports, and future scope. The system is intended to automate processes like membership registration, book issuing/returning, tracking book inventory and member records. It will leverage ASP.NET and SQL Server for development.
The GPT-3 model architecture is a transformer-based neural network that has been fed 45TB of text data. It is non-deterministic, in the sense that given the same input, multiple runs of the engine will return different responses. Also, it is trained on massive datasets that covered the entire web and contained 500B tokens, humongous 175 Billion parameters, a more than 100x increase over GPT-2, which was considered state-of-the-art technology with 1.5 billion parameters.
This document provides a feasibility report for an online university hostel management system. It discusses the problem definition, proposed solution, functionality requirements, and various feasibility aspects of the project such as technical, economic, and operational feasibility. It also covers requirements analysis, software configuration, system implementation, and provides a conclusion. The key functionality of the system includes modules for administration, hostel management, and students to manage activities like bookings, bills, meal ordering, and notices.
This document discusses harnessing large language models (LLMs) for business applications. It provides an overview of how LLMs have progressed from foundational models to today's large language models. The document then discusses several potential use cases for LLMs in business, including for sales. It notes that LLMs have potential benefits but also risks like lack of transparency, bias, and unreliability that must be addressed. The document proposes a framework for assessing the feasibility of LLMs for different business uses.
This document describes a project to develop an online help desk system for a college campus. A team of 4 students submitted the project to fulfill their degree requirements. The system will allow administrators, faculty, and students to log service requests for various campus facilities online. It will streamline the workflow for managing and resolving issues. Key aspects of the system include user registration and authentication, querying facilities, viewing notices, and live chat. The project uses MySQL, PHP, and Dreamweaver for the development.
This presentation gives an introduction about different types of information systems, the information system's development methodologies and required infrastructures.
The main objective of this project is to build a website which will help farmers from Indian villages to sell their products. Here if suppose some village farmers want to use this facility and want to learn how is it possible and how they can use e-farming to sell their products
This document outlines a graduation project to design an interactive rehabilitation game for people with hemispatial neglect. The project will involve researching the disability, consulting with doctors and care workers, visiting rehabilitation centers, designing the game, conducting playtesting at school and rehabilitation centers, and surveying participants.
The document discusses analyzing the business case for IT systems projects. It explains that the systems planning phase involves reviewing proposals to determine if they present a strong business case. Analysts must consider the company's mission, objectives and IT needs. The process starts with a systems request and preliminary investigation to evaluate feasibility, fact finding, and reporting to management. Setting project priorities involves rejecting infeasible requests and prioritizing remaining items based on greatest benefit, lowest cost and shortest timeline.
The document is a summary of a student's hostel management system project. It includes acknowledgements, an abstract, table of contents, introduction, system analysis, design, implementation, testing, and conclusion sections. The introduction defines the problems with existing manual hostel management systems and the objectives of the proposed computerized system. The system analysis compares the existing and proposed systems. The proposed system aims to automate processes, provide quick access to accurate information, and reduce costs and errors compared to the manual system. The system design and implementation sections describe the hardware, software, database tables, user interfaces, and coding used to develop the project.
All Actors of the System
Subsystems of the system
Use case with all actors with all subsystem
Separate use case diagram of all subsystems with all actors
Separate table of all use case of all sub systems with actors
Define the action of actors and system response for all use case.
The document describes a graphics editor program that simulates the MS Paint application. It uses OpenGL for graphics rendering and GLUT for creating windows and rendering scenes. Key features implemented include tools for drawing shapes, images, and text. OpenGL functions are used for rendering while GLUT functions handle window creation and events. The design section covers header files, OpenGL/GLUT functions, and user-defined functions for tasks like drawing, erasing, and filling shapes. Implementation details are provided for various drawing algorithms and user interface elements.
Library mangement system project srs documentation.docjimmykhan
The document describes a library management system created in Java. It has four main modules: inserting data into the database, extracting data from the database, generating reports on borrowed and available books, and a search facility. The proposed system automates library processes like adding members and books, searching, borrowing and returning books. This makes transactions faster and reduces errors compared to the manual existing system. The system was implemented using Java, MS Access for the database, and designed to run on Windows operating systems. Testing was done to check functionality and ensure all requirements were met.
This file contains full report of online fitness gym.And it was prepare by Abhishek, Saurav and Jitendra. If any query please contact at abhishek96patel@gmail.com
General Meeting: "Opening a pandora's box"
Deepasri Dattaraghava and Annya Satyaviana on February 10, 2023
Join us for a thought-provoking meeting where we will all delve into the question of whether ChatGPT and other language models are doing more harm than good.
The event will feature keynote speakers, panel discussions, and interactive sessions that will explore the impact of AI on society, ethics, and the future of work.
Come ready to collaborate and discuss. Attendees will have the opportunity to engage with experts in AI and the broader university community to gain a deeper understanding of the potential dangers and benefits of advanced AI technologies.
Don't miss this opportunity to be part of the important conversation around the role of AI in our world.
This session was presented at the AWS Community Day in Munich (September 2023). It's for builders that heard the buzz about Generative AI but can’t quite grok it yet. Useful if you are eager to connect the dots on the Generative AI terminology and get a fast start for you to explore further and navigate the space. This session is largely product agnostic and meant to give you the fundamentals to get started.
The document provides details about a library management system project done by Sumedh Kumar Singh at MECON Limited, Ranchi under the guidance of Mr. P.K. Dubey. The project report includes sections on feasibility study, system architecture, database creation and tables, forms design, and deployment. The proposed system automates processes like book and member management, book issuing and returning, and calculates any fines. It aims to provide efficient services to users and reduce the workload for library staff.
The document discusses the importance of operating system (OS) security and the challenges involved. It notes that OSes control hardware access and scheduling, so flaws can compromise all security. Modern OSes are multi-user and multi-tasking, requiring protection of processes, memory, I/O devices, and more. Key OS security functions include memory protection, file protection, authentication, and authorization. Mechanisms like separation, access controls, and complete mediation are important to enforce security policies.
The document outlines the scope and design of a library management system. It includes sections on project purpose, scope, assumptions, functionality, specific requirements, tools/platform, resources used, design specification including entity relationship and data flow diagrams, database structure, module description, process logic, types of reports, and future scope. The system is intended to automate processes like membership registration, book issuing/returning, tracking book inventory and member records. It will leverage ASP.NET and SQL Server for development.
The GPT-3 model architecture is a transformer-based neural network that has been fed 45TB of text data. It is non-deterministic, in the sense that given the same input, multiple runs of the engine will return different responses. Also, it is trained on massive datasets that covered the entire web and contained 500B tokens, humongous 175 Billion parameters, a more than 100x increase over GPT-2, which was considered state-of-the-art technology with 1.5 billion parameters.
This document provides a feasibility report for an online university hostel management system. It discusses the problem definition, proposed solution, functionality requirements, and various feasibility aspects of the project such as technical, economic, and operational feasibility. It also covers requirements analysis, software configuration, system implementation, and provides a conclusion. The key functionality of the system includes modules for administration, hostel management, and students to manage activities like bookings, bills, meal ordering, and notices.
This document discusses harnessing large language models (LLMs) for business applications. It provides an overview of how LLMs have progressed from foundational models to today's large language models. The document then discusses several potential use cases for LLMs in business, including for sales. It notes that LLMs have potential benefits but also risks like lack of transparency, bias, and unreliability that must be addressed. The document proposes a framework for assessing the feasibility of LLMs for different business uses.
This document describes a project to develop an online help desk system for a college campus. A team of 4 students submitted the project to fulfill their degree requirements. The system will allow administrators, faculty, and students to log service requests for various campus facilities online. It will streamline the workflow for managing and resolving issues. Key aspects of the system include user registration and authentication, querying facilities, viewing notices, and live chat. The project uses MySQL, PHP, and Dreamweaver for the development.
This presentation gives an introduction about different types of information systems, the information system's development methodologies and required infrastructures.
The main objective of this project is to build a website which will help farmers from Indian villages to sell their products. Here if suppose some village farmers want to use this facility and want to learn how is it possible and how they can use e-farming to sell their products
This document outlines a graduation project to design an interactive rehabilitation game for people with hemispatial neglect. The project will involve researching the disability, consulting with doctors and care workers, visiting rehabilitation centers, designing the game, conducting playtesting at school and rehabilitation centers, and surveying participants.
This document discusses the use of artificial intelligence techniques in education. It outlines different AI methods like fuzzy logic, case-based reasoning, rule-based expert systems, and Bayesian networks that have been applied in educational systems. Some examples of applications are computer-aided instruction, learning management systems, intelligent tutoring systems, and an intelligent Pascal tutoring system. The conclusion states that AI has been widely used in education by applying techniques to simulate human intelligence and help teach students.
Ahmed Muhammad Abd-Elkader Shehab is an Egyptian civil engineer who graduated from Alexandria University in 2016. He has extensive experience in internships with construction and petroleum companies. Shehab has strong computer skills and is proficient in English, Arabic, and basic French. He has participated in several extracurricular activities and humanitarian projects during his time at university.
Presentation skills for Graduation projectsmohamedsamyali
The document provides tips for giving effective presentations. It advises the presenter to know their goals and audience, focus on what matters most by emphasizing goals and removing distractions, be professional in appearance and manner, and be confident through preparation and enthusiasm. Key points include understanding the audience's background and expectations, matching the presentation style and level of detail to the goal of informing, persuading, or reporting, and answering questions professionally while staying focused on the topic.
The document outlines requirements for a cumulative career-based graduation project for students. It is intended to help students research potential careers and educational programs. Students must complete grade-level assignments each year, saving their work to an electronic portfolio. They will meet twice yearly with a mentor to discuss progress. Failure to complete an assignment results in consequences like restricted privileges and risk of not graduating.
This document outlines the requirements for a senior graduation project for an AP Literature class. Students must complete an 8-10 page research paper on a controversial topic, citing at least 5 web/article sources and 2 book sources. They will interview someone related to their topic and include a transcript of the interview in their paper. In addition to the paper, students must create a product, give an 8-10 minute presentation to a panel, and put together a portfolio documenting their work. The portfolio, final product, and presentation are due between May 1-11.
This document provides information and guidance for students on completing their graduation project over the summer. It recommends using the summer months to spread out and potentially finish the required hours, as extracurricular activities make it difficult during the school year. All 11th grade students will write their graduation project paper in English class in September, so hours must be completed beforehand. The document outlines the requirements, forms, and timeline for community service, job shadowing, and creative work pathways. It also provides resources like the graduation project LibGuide for finding summer opportunities and getting professional critiques.
The document provides guidance on writing a graduation project, including formatting requirements such as using A4 paper, 1.5 line spacing, and Times New Roman 14 point font. It outlines the necessary sections of the project such as the title page, abstract, acknowledgments, contents, and references. The document also discusses finding information for the project through resources like textbooks, organizations, electronic journals, search engines, and PubMed.
Game AI 101 - NPCs and Agents and Algorithms... Oh My!Luke Dicken
This is a session originally written for students at Bradley University (Peoria, IL).
It covers a very high level introduction to the concepts behind Game AI, and includes some examples of how we can begin to make characters in a game world perform actions and appear to be making intelligent decisions.
This document discusses different aspects of tariffs for electricity supply including objectives, types of tariffs, and key terms. It describes five main types of tariffs - simple, flat rate, block rate, two part, and maximum demand tariffs. It also covers related concepts like connected load, maximum demand, demand factor, diversity factor, load factor, reserves, load curves, and load duration curves.
Artificial Intelligence in Computer and Video GamesLuke Dicken
This lecture was given at the April meeting of the Glasgow branch of the British Computer Society on 12th April 2010. The lecture was supposed to be given by Dr. Darryl Charles, who fell ill a couple of days before the event, and I was asked to take the lecture instead.
In the presentation I cover the basics of why AI and Games are well suited and give a brief discussion of different types of AI as I see it. I discuss briefly how AI fits into the context of the game in terms of execution.
The bulk of the talk presents case studies in the format of Commercial game -> Theoretical technique used -> Research project using this technique.
It should be noted that the section on Left4Dead was omitted from the lecture as it was presented at the time due to concerns about the length
This document discusses artificial intelligence in games. It begins by defining artificial intelligence as making computers able to perform thinking tasks like humans and animals. It then discusses the importance of AI in games, noting that modern games require not just good graphics but also intelligent opponents. The document outlines some key aspects of designing game AI, like movement, decision making, and perception. It provides examples of how AI is implemented in common game genres like first-person shooters. It concludes by stating that AI design is complex and creative, and hopes for continued innovation in the field.
The document discusses various techniques used for artificial intelligence in gaming. It describes how state machines and planning systems are used to simulate human behavior for non-player characters. State machines define a character's states and transitions between states, but have limitations. Planning systems allow characters to work backwards from objectives to determine paths and behaviors. Additional techniques include navigation meshes to guide character movement and online learning from player data. The goal is to improve gaming experiences by making characters seem intelligent through these simulated human behavior methods.
Game playing in artificial intelligent technique syeda zoya mehdi
The document discusses game artificial intelligence and techniques used to generate intelligent behavior in non-player characters in computer and video games. It covers topics like machine learning, reinforcement learning, pathfinding algorithms, and different data structures used to represent game boards and chess positions. Game AI aims to create behavior that feels natural to the player while obeying the rules of the game. Various computer science disciplines are required to develop effective game AI, and different types of games require different AI techniques.
This document discusses power factor improvement through the use of capacitors. It begins with definitions of key terms like active power, reactive power, and apparent power. It then discusses how inductive loads cause low power factors and the disadvantages of low power factors, such as increased current and line losses. The document presents methods for calculating the capacitance needed to improve the power factor of an inductive load. It also provides examples of typical power factors for various equipment and industries. Overall, the document provides an overview of power factors and how capacitors can be used to improve power factors.
The document discusses the key differences between creative and technical writing. Technical writing aims to convey objective scientific or technical information for a specific purpose and audience. It uses precise, concise language without emotion-evoking words. Technical writing follows basic principles like clearly stating the purpose and conclusions and using a logical structure with supporting data. The document also provides examples of technical writing formats and materials.
ENG 131: Technical Writing Introduction PowerPointElizabeth Lohman
The document is a PowerPoint presentation that defines technical writing and compares it to academic writing. It states that technical writing aims to convey information clearly and directly so readers can access specific details easily. In contrast, academic writing may lack a clear purpose and use more complex language and structure. The presentation also notes key differences in purpose, format, and language between the two styles of writing.
This document presents an overview of reactive power compensation. It defines reactive power compensation as managing reactive power to improve AC system performance. There are two main aspects: load compensation to increase power factor and voltage regulation, and voltage support to decrease voltage fluctuations. Several methods of reactive power compensation are discussed, including shunt compensation using capacitors and reactors, series compensation, static VAR compensators (SVCs), static compensators (STATCOMs), and synchronous condensers. SVC and STATCOM technologies are compared, with STATCOMs having advantages of smaller components, better control, and transient response.
This document provides an overview of an adaptive AI engine project for real-time strategy (RTS) games. It discusses what game AI is, why an AI engine is needed, and the common structures of AI engines. It also outlines elements that require AI in RTS games, areas needing improvement, and common techniques used in AI engines, including decision making, planning, and learning approaches. The document notes that AI development has been slow in RTS games due to challenges like imperfect information and fast-paced action. It identifies several areas needing more research, such as adversarial planning, learning, and spatial/temporal reasoning. Recent papers on the topic focus on planning, reinforcement learning, genetic algorithms, and hybrid approaches.
This is a group assignments, I am assigned to do only the SWOT AND.docxjuliennehar
This is a group assignments, I am assigned to do only the SWOT AND PORTER’S FIVE FORCES for both USA and China.
The topic we are going to talk about is Facebook whether to go back to China
https://www.cnbc.com/2017/09/19/facebook-to-enter-china-next-year-analyst-predicts.html
I will need 1.5 pages about the SWOT and Porters five forces analysis, also I need the bullet points of what you wrote for the SWOT and porter’s five forces, best as following, make a table or something. (no introduction about the article or the situation needed, someone else will do that, just the analysis of swot and porters five forces of usa and china)
The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19)
Hierarchical Macro Strategy Model for
MOBA Game AI
Bin Wu
Tencent AI Lab
[email protected]
Abstract
The next challenge of game AI lies in Real Time Strategy
(RTS) games. RTS games provide partially observable gam-
ing environments, where agents interact with one another in
an action space much larger than that of GO. Mastering RTS
games requires both strong macro strategies and delicate mi-
cro level execution. Recently, great progress has been made
in micro level execution, while complete solutions for macro
strategies are still lacking. In this paper, we propose a novel
learning-based Hierarchical Macro Strategy model for mas-
tering MOBA games, a sub-genre of RTS games. Trained
by the Hierarchical Macro Strategy model, agents explicitly
make macro strategy decisions and further guide their micro
level execution. Moreover, each of the agents makes indepen-
dent strategy decisions, while simultaneously communicat-
ing with the allies through leveraging a novel imitated cross-
agent communication mechanism. We perform comprehen-
sive evaluations on a popular 5v5 Multiplayer Online Battle
Arena (MOBA) game. Our 5-AI team achieves a 48% win-
ning rate against human player teams which are ranked top
1% in the player ranking system.
Introduction
Light has been shed on artificial general intelligence after
AlphaGo defeated world GO champion Lee Seedol (Silver
et al. 2016). Since then, game AI has drawn unprecedented
attention from not only researchers but also the public. Game
AI aims much more than robots playing games. Rather,
games provide ideal environments that simulate the real
world. AI researchers can conduct experiments in games,
and transfer successful AI ability to the real world.
Although AlphaGo is a milestone to the goal of general
AI, the class of problems it represents is still simple com-
pared to the real world. Therefore, recently researchers have
put much attention to real time strategy (RTS) games such
as Defense of the Ancients (Dota) (OpenAI 2018a) and Star-
Craft (Vinyals et al. 2017; Tian et al. 2017), which represents
a class of problems with next level complexity. Dota is a fa-
mous set of science fiction 5v5 Multiplayer Online Battle
Arena (MOBA) games. Each player controls one unit and
cooperate with four allies to d ...
This document outlines a project to develop an adaptive intelligent agent for real-time strategy games. The project aims to make the computer opponent more human-like by overcoming issues like predictability, non-adaptability, and inability to learn from past experiences. The project will use techniques like reinforcement learning, case-based planning and BDI agents. It will develop the AI engine for the open-source game BosWars. The expected deliverables are an enhanced AI engine and experimental results comparing it to standard AI.
This document outlines a project to develop an adaptive intelligent agent for real-time strategy games. It discusses the theoretical areas of learning, planning and knowledge sharing. The problems with current computer opponents being predictable, non-adaptive, and relying on static scripts are defined. The objectives are to create an adaptive AI using techniques like reinforcement learning, case-based planning and BDI agents. The document reviews related work and outlines the project timeline and deliverables which include an enhanced AI engine and experimental results comparing it to ordinary static AI.
1st Seminar- Intelligent Agent for Medium-Level Artificial Intelligence in Re...Muhamad Hesham
This document presents an introduction to a project on developing a medium-level artificial intelligence agent for real-time strategy games. The project members and supervisors are listed. The agenda discusses the problem domain of RTS games, defining the need for a medium-level AI to bridge high-level and low-level control, and the objectives to mimic human reasoning and planning. Motivations for the research include interests in RTS games and applications for war simulation. Approaches to be investigated include case-based planning and reinforcement learning. The agent will be tested on the Wargus RTS game using C++ and evaluated by RTS experts.
Game playing is one of the most studied areas of artificial intelligence. Game AI techniques produce intelligent behavior in video game characters. These techniques include pathfinding, decision making, planning, and developing agents that can match or exceed human performance. Game playing provides a test bed for AI ideas because games have well-defined rules and provide challenges in developing rational agents.
This document discusses and compares several artificial intelligence techniques used in computer games: finite state machines, scripting, agents, flocking, and genetic algorithms. It provides an overview of each technique, including how it can be applied to games and examples of commercial games that use each technique. The document also evaluates the effectiveness and future role of these techniques in the game industry. It concludes that while current games predominantly use simpler techniques like finite state machines and scripting, game developers will need to incorporate more advanced techniques like genetic algorithms to develop characters with more realistic and adaptive behavior.
This document provides an introduction to artificial intelligence and how it can be applied to games. It discusses what AI is, common AI fields like machine learning and computer vision. It then focuses on AI for games, describing the components of an abstract AI agent model including sensors, actuators, and the environment. Actuators can include pathfinding, decision making and steering behaviors. The environment provides information to agents and can include resources, terrain and other units' positions. Finally, it outlines steps for building an AI game, such as determining the game type, choosing tools, designing objects, determining the number of agents, and separating agents from the environment.
Learning to Reason in Round-based Games: Multi-task Sequence Generation for P...Deren Lei
Sequential reasoning is a complex human ability, with extensive previous research focusing on gaming AI in a single continuous game, round-based decision makings extending to a sequence of games remain less explored. CounterStrike: Global Offensive (CS:GO), as a round-based game with abundant expert demonstrations, provides an excellent environment for multi-player round-based sequential reasoning. In this work, we propose a Sequence Reasoner with Round Attribute Encoder and Multi-Task Decoder to interpret the strategies behind the round-based purchasing decisions. We adopt few-shot learning to sample multiple rounds in a match, and modified model agnostic meta-learning algorithm Reptile for the meta-learning loop. We formulate each round as a multi-task sequence generation problem. Our state representations combine action encoder, team encoder, player features, round attribute encoder, and economy encoders to help our agent learn to reason under this specific multi-player round-based scenario. A complete ablation study and comparison with the greedy approach certify the effectiveness of our model. Our research will open doors for interpretable AI for understanding episodic and long-term purchasing strategies beyond the gaming community.
This document provides information about the course Code 22MCA262. It includes details like CIE Marks (50), Teaching Hours (2:0:2), SEE Marks (50), Total Hours of Pedagogy (40), Total Marks (100), Credits (03), and Exam Hours (03). The document then discusses 5 key modules that will be covered in the course: 1) Introduction to AI and Production Systems, 2) Introduction to Artificial Intelligence, 3) History of AI, 4) Application of AI, and 5) Intelligent Robots. It provides overviews and examples for each module topic.
Artificial intelligence (AI) is a branch of computer science that aims to help machines solve complex problems like humans by borrowing characteristics from human intelligence. AI has many applications in business including credit screening, risk assessment, forecasting, portfolio management, customer analytics, and human resources. The future of AI could include intelligent personal robots and autonomous vehicles networked together. While AI may replace some human jobs, it will likely produce more applications and augment human capabilities rather than replace humans altogether.
Libratus is an AI developed by researchers at Carnegie Mellon University that achieved superhuman performance at no-limit Texas hold'em poker by defeating top human professionals in a 120,000-hand poker competition. It uses a three-part approach: 1) It computes an abstraction of the full game to develop a "blueprint" strategy for early rounds; 2) When later rounds are reached, it constructs finer-grained abstractions in real-time and solves them while ensuring strategies fit the overall blueprint; 3) It enhances the blueprint by adding missing branches and strategies based on opponents' actual moves. This game-theoretic approach uses application-independent techniques and marks the first time an AI has defeated humans at this
This document provides an overview of artificial intelligence and multimedia in computer games. It discusses the history and definitions of AI, how hardware developments have enabled greater AI capabilities in games, and techniques like rule-based systems and learning. It also covers the usage of AI in games for techniques like finite state machines and genetic algorithms. The document then discusses the role of multimedia elements like sound effects. It concludes by predicting future advances will focus on more realistic AI behaviors and more sophisticated graphics processors.
This presentation outlines the basics of game analytics and the symbiotic relationship between game analytics and game user research, and provides 10 examples of cool game analytics and game data mining methods applied across the board of indie to AAA titles.
Artificial intelligence AI is the intelligence exhibited by an artificial entity, generally assumed to be a computer. It has been involved with gaming since day one. It is progressively being widely used in the gaming industry. AI in games is commonly used for creating players opponents. It is the foundation of all video games. Games like Nim, checkers, or chess took advantage of smart algorithms to beat human players. AI based games are based on a finite set of actions or reactions whose sequence can be easily predicted by expert players. This paper provides an introduction on the applications of AI in different games. Matthew N. O. Sadiku | Sarhan M. Musa | Abayomi Ajayi-Majebi "Artificial Intelligence in Gaming" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38516.pdf Paper Url: https://www.ijtsrd.com/engineering/electrical-engineering/38516/artificial-intelligence-in-gaming/matthew-n-o-sadiku
Inside Story on HPC’s Role in Bridges Strategic Reasoning Research Project at...Dana Gardner
Transcript of a discussion on how Carnegie Mellon University researchers are advancing strategic reasoning and machine learning capabilities using the latest in high performance computing.
This document discusses the development of an open world action-adventure game called R.A.W - The Game using Unreal Engine 5. Unreal Engine 5 incorporates the Lumen global illumination system and Nanite virtualized geometry system to enable high-fidelity graphics. Lumen allows dynamic lighting and reflections at large scales. Nanite renders massive high-polygame assets with pixel-level detail. The game is being developed in C++ using tools like Blender for 3D modeling. Unreal Engine 5's advanced rendering capabilities allow the creation of highly detailed, complex and realistic game worlds with improved performance.
1. Game playing is one of the most studied areas of artificial intelligence as games provide test beds for developing techniques that are useful in other domains.
2. Common techniques used in game AI include machine learning, pathfinding algorithms, behavior trees, and search algorithms like minimax and alpha-beta pruning.
3. Game AI has applications beyond entertainment, including in training simulators, economic simulations, and military simulations. Developments in game AI have contributed to advances in other fields like DNA sequencing and scheduling.
This document provides an introduction and overview of the CoEng5131: Artificial Intelligence course. The course is taught by instructor Yasabneh T. Atnafu at BiT, BDU in 2024. It covers topics including what AI is, what AI can do, rational decision making, natural language, vision, robotics, logic, and designing rational agents. Prerequisites for the course include an intermediate programming course and a reasoning skills course. Coursework will involve programming projects in Python groups and homework assignments, along with a midterm and final exam.
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1. Adaptive AI Engine for RTS Games Introduction to the Project AbdelRahmanAl Ogail Omar Khaled Enayet Under the Supervision Of : Dr. Ibrahim Fathy Moawad
2. Agenda What’s Game AI? Why AI Engine? Structure of AI Engine What are RTS Games? Elements That Need AI in RTS Games Areas That Need Improvement in RTS AI Common Used Techniques in AI Engine So why working on that project (what’s new)?
3. Agenda Why is AI Development slow in RTS Games. AI Areas needing more research in RTS Games. Latest Research Introduction. Research Papers and Theses. Introduction The Papers : Intro Case-Based Planning. Reinforcement Learning. Genetic Algorithms. Hybrid Approaches. Opponent Modeling Approaches. Misc. Approaches.
4. What’s Game AI? Let the computer think Goal of Game AI: Entertainment NOT perfection How that guy finds the right answer? Deeper Blue Example
7. What are RTS Games ? Real-Time-Strategy (RTS) games can be viewed as simplified military simulations. Several players struggle over resources scattered over a terrain by setting up an economy, building armies, and guiding them into battle in real-time. The current AI performance in commercial RTS games is poor by human standards. They are characterized by enormous state spaces, large decision spaces, and asynchronous interactions. RTS games also require reasoning at several levels of granularity, production-economic facility (usually expressed as resource management and technological development) and tactical skills necessary for combat confrontation.
8. Elements That Need AI in RTS Games Workers (peons, gatherers) Individual units (soldiers, tanks…) Town building: how to build my town to max. benefits Pathfinding What’s the best (not shortest) way to get from A to B
9. Elements That Need AI in RTS Games Low level strategies Which pathfinding algorithm I should use? Medium level strategies How to achieve high level strategies? High level strategies What are my goals?
10. Elements That Need AI in RTS Games Terrain Analysis (keep track of your enemy) Opponent Modeling (know your enemy) Resource Management (take the control) Diplomacy Systems (always have allies)
11. Areas That Need Improvement in RTS AI Determine when AI element is stuck Opponent modeling More strategies less tactics Construct consistent army (solders, tanks, planes) Think about support lines How to retreat Setup and detect ambushes
12. Areas That Need Improvement in RTS AI Learning Some areas of learning: AI opponent get in the same trap repeatedly Know safe map locations and get away from kill zones Know how human player attacks and which units he favors Does the player rushes ? Does the player rely on units that require certain resources? Does he frequently build a number of critical structures in a poorly defensive place? Are his attacks balanced? ( rock, paper, scissors example)
13. Common Used Techniques Categories of Used Techniques: Decision Making Other Techniques Data-Driven Techniques Perception Techniques Communication Techniques
14. Decision Making – Finite State Machine When to use: to represent states
15. Decision Making – Fuzzy State Machine When to use: to represent several states at the same time
16. Decision Making – Genetic Algorithms Used to find best solutions to a given problems Genetic Process Rely on the idea of reproduction Example of using: finding best optimal # of peons working in each areas (area = building, money, wood, stone…)
17. Decision Making – Neural Networks Rely on simulating human brain Used in: Classification Opponent modeling
18. Decision Making – Artificial Life ALife is about searching to find “governing principles” to the life Newton theorem Alife Techniques: Cellular Automata Steering Behaviors Add the creativity to the AI opponent
19. Decision Making – Steering Behaviors Simple rules that produces emergent behaviors Boids research by Craig Reynolds Used: To simulate real life In producing emergent behavior Provide autonomies agents
20. Decision Making – Planning Planning is, deciding upon a course of action before acting Usage in games: Pathfinding algorithms Set plans to high level strategies in RTS Games anticipating ambushes Some of Planning Techniques: A*, Mean & Analysis, Patch Recalculation, Minimax
21. Decision Making – Production Systems As prolog Used techniques: Forward changing Backward changing
22. Decision Making – Decision Trees Complex IF-ELSE Statements represented as tree Usage if games: Player modeling High level strategies
23. Other Techniques – Data Driven AI Scripting Systems Using an external resource (not coded) that controls the AI opponent Advantage Add extendibility to the game
24. Other Techniques - Messaging Supplies communication between game objects
25. Other Techniques – LBI Systems LBI: Location Based Information Systems It’s a perception technique Keeps track of the world attributes Common techniques: Influence Maps Terrain Analysis Smart Terrain
26. Other Techniques – LBI Systems Usage in games: Helps with obstacle avoidance Detecting player, resources places Danger specification (keep track of kill zones) Discover critical points in the world (as bridges)
27. What’s new? Future of wars is going to be more robotic Sharing & validating plans MIT asks for researches in this area (10-2008) Alex J.C. said: “there’s no real learning and adaptation in commercial games” Researches in this area is so active! Papers Range from 2003-2009
28. Why is AI Development slow in RTS Games ? RTS game worlds feature many objects, imperfect information, micro actions, and fast-paced action. By contrast, World–class AI players mostly exist for slow– paced, turn–based, perfect information games in which the majority of moves have global consequences and planning abilities therefore can be outsmarted by mere enumeration. Market dictated AI resource limitations. Up to now popular RTS games have been released solely by game companies who naturally are interested in maximizing their profit. Because graphics is driving games sales and companies strive for large market penetration only about 15% of the CPU time and memory is currently allocated for AI tasks. On the positive side, as graphics hardware is getting faster and memory getting cheaper, this percentage is likely to increase – provided game designers stop making RTS game worlds more realistic. Lack of AI competition. In classic two–player games tough competition among programmers has driven AI research to unmatched heights. Currently, however, there is no such competition among real–time AI researchers in games other than computer soccer. The considerable man–power needed for designing and implementing RTS games and the reluctance of game companies to incorporate AI APIs in their products are big obstacles to AI competition in RTS games.
29. AI Areas needing more research Adversarial real–time planning. In fine–grained realistic simulations, agents cannot afford to think in terms of micro actions such as “move one step North”. Instead, abstractions of the world state have to be found that allow AI programs to conduct forward searches in a manageable abstract space and to translate found solutions back into action sequences in the original state space. Because the environment is also dynamic, hostile, and smart — adversarial real–time planning approaches need to be investigated. Decision making under uncertainty. Initially, players are not aware of the enemies’ base locations and intentions. It is necessary to gather intelligence by sending out scouts and to draw conclusions to adapt. If no data about opponent locations and actions is available yet, plausible hypotheses have to be formed and acted upon. Opponent modeling, learning. One of the biggest shortcomings of current (RTS) game AI systems is their inability to learn quickly. Human players only need a couple of games to spot opponents’ weaknesses and to exploit them in future games. New efficient machine learning techniques have to be developed to tackle these important problems.
30. AI Areas needing more research (2) Spatial and temporal reasoning. Static and dynamic terrain analysis as well as understanding temporal relations of actions is of utmost importance in RTS games — and yet, current game AI programs largely ignore these issues and fall victim to simple common–sense reasoning . Resource management. Players start the game by gathering local resources to build up defenses and attack forces, to upgrade weaponry, and to climb up the technology tree. At any given time the players have to balance the resources they spend in each category. For instance, a player who chooses to invest too many resources into upgrades, will become prone to attacks because of an insufficient number of units. Proper resource management is therefore a vital part of any successful strategy
31. AI Areas needing more research (3) Collaboration. In RTS games groups of players can join forces and intelligence. How to coordinate actions effectively by communication among the parties is a challenging research problem. For instance, in case of mixed human/AI teams, the AI player often behaves awkwardly because it does not monitor the human’s actions, cannot infer the human’s intentions, and fails to synchronize attacks.
33. Latest Research : Intro. Current Implementation of RTS Games applies extensive usage of FSM that makes them highly predictable. Adaptation is achieved either through Learning or planning or a mixture of both Planning is beginning to appear in commercial games such as DemiGod and Latest Total War Game. Learning has limited success so far. Developers are experimenting on replacing the ordinary decision making systems (FSM, FUSM, Scripting, Decision Trees, and Markov Systems) with Learning Techniques
34. Latest Research : The Papers More than 30 papers/theses talk about Planning and Learning in RTS Games The Major 3 approaches to AI Research in RTS-GAMES concerning Learning and Planning are Case-Based Planning, Reinforcement Learning with its different techniques and Genetic Algorithms. Some Papers use a Hybrid approach of these techniques. Others use other planning algorithms like PDDL or opponent modeling techniques and other misc. techniques. 3 papers encourage the research in this field. 9 papers use Case-Based Planning Approach from 2003-2009,1 uses a Hybrid CBR/GA approach in 2008,1 uses a Hybrid CBR/RL approach in 2007 10 papers use Reinforcement Learning with its different forms (Monte-Carlo, Dynamic Scripting and TD-Learning),1 uses TD-Learning with GA,1 uses Dynamic Scripting with GA 3 Papers use Genetic Algorithms. 3 Papers apply opponent modeling techniques.
35. Encouraging Research : Papers RTS Games and Real–Time AI Research – 2003 RTS Gaines A New AI Research Challenge – 2003 Call for AI Research in RTS Games - 2004
36. Case-Based Planning Case-based planning is the reuse of past successful plans in order to solve new planning problems. It’s an application of Case-Based Reasoning in planning.
37. Case-Based Planning : Papers The David Aha Research Thread : On the Role of Explanation for Hierarchical Case-Based Planning in RTS Games - after 2004 Learning to Win - Case-Based Plan Selection in a RTS Game- 2005 Defeating Novel Opponents in a Real-Time Strategy Game – 2005 The Santiago Ontanon Research Thread : Case-Based Planning and Execution for RTS Games – 2007 Learning from Human Demonstrations for Real-Time Case-Based Planning – 2008 On-Line Case-Based Plan Adaptation for RTS Games- 2008 Situation Assessment for Plan Retrieval in RTS Games – 2009 Other Papers Case-based plan recognition for RTS games - after 2003 Mining Replays of RTS Games to learn player strategies – 2007
38. Reinforcement Learning It is a sub-area of machine learning concerned with how an agent ought to take actions in an environment so as to maximize some notion of long-term reward. Reinforcement learning differs from the supervised learning problem in that correct input/output pairs are never presented, nor sub-optimal actions explicitly corrected. Further, there is a focus on on-line performance, which involves finding a balance between exploration and exploitation.
39. Reinforcement Learning : Papers Dynamic Scripting : Goal-Directed Hierarchical Dynamic Scripting for RTS Games – 2006 Automatically Acquiring Domain Knowledge For Adaptive Game AI Using Evolutionary Learning – 2008 Monte-Carlo Planning : UCT(Monte-Carlo) for Tactical Assault Battles in Real-Time Strategy Games. – 2003 Monte Carlo Planning in RTS Games - After 2004 Temporal-Difference Learning : Learning Unit Values in Wargus Using Temporal Differences – 2005 Establishing an Evaluation Function for RTS games - After 2005 Dynamic Scripting VS Monte-Carlo Planning: Adaptive reinforcement learning agents in RTS games – 2008 Hierarchical Reinforcement Learning Hierarchical Reinforcement Learning in Computer Games - After 2006 Hierarchical Reinforcement Learning with Deictic repr. in a computer game- After 2006
40. Genetic Algorithms Genetic algorithms are a particular class of evolutionary algorithms (EA) that use techniques inspired by evolutionary biology such as inheritance, mutation, selection, and crossover.
41. Genetic Algorithms : Papers Human-like Behavior in RTS Games – 2003 Co-evolving Real-Time Strategy Game Playing Influence Map Trees with genetic algorithms Co-Evolution in Hierarchical AI for Strategy Games - after 2004
42. Hybrid Approaches : Papers Genetic Algorithms + Dynamic Scripting : Improving Adaptive Game AI With Evolutionary Learning – 2004 Automatically Acquiring Domain Knowledge For Adaptive Game AI using Evolutionary Learning – 2005 Genetic Algorithms + TD-Learning : Neural Networks in RTS AI – 2001 Genetic Algorithms + Case-Based Planning : Stochastic Plan Optimization in Real-Time Strategy Games – 2008 Case-Based Reasoning + Reinforcement Learning : Transfer Learning in Real-Time Strategy Games Using Hybrid CBR-RL - 2007
43. Opponent Modeling : Papers Hierarchical Opponent Models for Real-Time Strategy Games – 2007 Opponent modeling in real-time strategy games - after 2007 Design of Autonomous Systems - Learning Adaptive playing a RTS game - 2009
44. Misc. Approaches : Papers Supervised Learning : Player Adaptive Cooperative Artificial Intelligence for RTS Games – 2007 PDDL : A First Look at Build-Order Optimization in RTS games - after 2006 Finite-State Machines : SORTS - A Human-Level Approach to Real-Time Strategy AI – 2007 Others : Real-time challenge balance in an RTS game using rtNEAT – 2008 AI Techniques in RTS Games -September 2006
46. References Books : AI Game Engine Programming -2009 Artificial Intelligence for Games – 2009 Papers: RTS Games and Real–Time AI Research –Michael Buro & Timothy M. Furtak - 2003 Call for AI Research in RTS Games - Michael Buro – 2004 Web Resources : AIGameDev Forums. GameDev.Net Forums. Wikipedia. Others