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Class lecture of Data Structure and Algorithms and Python.
Stack, Queue, Tree, Python, Python Code, Computer Science, Data, Data Analysis, Machine Learning, Artificial Intellegence, Deep Learning, Programming, Information Technology, Psuedocide, Tree, pseudocode, Binary Tree, Binary Search Tree, implementation, Binary search, linear search, Binary search operation, real-life example of binary search, linear search operation, real-life example of linear search, example bubble sort, sorting, insertion sort example, stack implementation, queue implementation, binary tree implementation, priority queue, binary heap, binary heap implementation, object-oriented programming, def, init
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Class lecture of Data Structure and Algorithms and Python.
Stack, Queue, Tree, Python, Python Code, Computer Science, Data, Data Analysis, Machine Learning, Artificial Intellegence, Deep Learning, Programming, Information Technology, Psuedocide, Tree, pseudocode, Binary Tree, Binary Search Tree, implementation, Binary search, linear search, Binary search operation, real-life example of binary search, linear search operation, real-life example of linear search, example bubble sort, sorting, insertion sort example, stack implementation, queue implementation, binary tree implementation, priority queue, binary heap, binary heap implementation, object-oriented programming, def, init
Knowledge representation In Artificial IntelligenceRamla Sheikh
facts, information, and skills acquired through experience or education; the theoretical or practical understanding of a subject.
Knowledge = information + rules
EXAMPLE
Doctors, managers.
It can bring the power of image recognition to CRM and third-party applications so that end users across sales, service, and marketing can discover new insights about their customers and predict outcomes that lead to smarter decisions.
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Full service Intellectual Property Law Firm in India| IPR Law Practice in India| Intellectual Property India, Intellectual Property Law, Indian IPR Lawyers
Knowledge representation In Artificial IntelligenceRamla Sheikh
facts, information, and skills acquired through experience or education; the theoretical or practical understanding of a subject.
Knowledge = information + rules
EXAMPLE
Doctors, managers.
It can bring the power of image recognition to CRM and third-party applications so that end users across sales, service, and marketing can discover new insights about their customers and predict outcomes that lead to smarter decisions.
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
help.mbaassignments@gmail.com
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Dear students get fully solved assignments
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call us at : 08263069601
Full service Intellectual Property Law Firm in India| IPR Law Practice in India| Intellectual Property India, Intellectual Property Law, Indian IPR Lawyers
Hi. I am Shahzad Pirzada. I am Sharing the beautiful places to visit in America. These places are the most attracting places for tourist and attract huge number of tourist every year. Shahzad Pirzada hopes that you guys will like these images.
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Dear students get fully solved assignments
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MODELLING OF INTELLIGENT AGENTS USING A–PROLOGijaia
Nowadays, research in artificial intelligence has widely grown in areas such as knowledge representation,
goal-directed behaviour and knowledge reusability, all of them directly relevant to improving intelligent
agents in computer games. In a particular way, we focus on the development of a novel algorithm that
allow an agent to combine fundamental theories such as reasoning, learning and simulation. This
algorithm combines a system of logical rules and a simulation mechanism based on learning that makes
our agent has an infallible mechanism for decision-making into the game “connect four”. The logic system
is developed in a modelling language known as Answer Set Programming or A–Prolog. This paradigm is
the integration of two well-known languages, namely Prolog and ASP.
Learn How to Become an Expert in Artificial Intelligence With Our Roadmap
Imagine a machine arranging all your clothes as you like it or preparing customized food, considering each family member’s choice. Interesting, Isn’t it? This is what we call Artificial Intelligence.
Artificial Intelligence in today’s world is entering every domain in our daily lives, and we can undoubtedly conclude that the future of technology is here. From various voice assistants to chatbots, over all these years, Artificial Intelligence has proved that it indeed is here to stay. So why not seize the opportunity and build a career out of it?
In this article, we will share a concise introduction to artificial intelligence and which skills can assist you in creating a vocation in this field. This is just a microscopic viewpoint of the explicit learn path, link of which is mentioned at the end of the article.
What is Artificial Intelligence?
Emerging technologies like Artificial Intelligence and Data Science have made our life easier. Artificial intelligence, or AI as it’s more commonly called, alludes to the reenactment of human insight in machines that are modified to think like and copy humans.
It is the development of computer systems that can perform tasks that predominantly require human intelligence. These include visual perception, decision-making, speech recognition, and language translation.
Educational Requirements
Artificial Intelligence is a highly demanding and skill-intensive field. Since it is related to computer science, it needs a certain level of technical expertise and technological know-how. Hence, before even starting with the learning process, the primary prerequisite you must meet is a Bachelor’s degree in fields relevant to Artificial Intelligence such as Computer Science, Engineering, Mathematics, Statistics, and Information Technology.
If you have a Bachelor’s degree in math-intensive fields such as Economics and Finance, that can help you kickstart your journey in Artificial Intelligence as well.
Knowledge Based Reasoning: Agents, Facets of Knowledge. Logic and Inferences: Formal Logic,
Propositional and First Order Logic, Resolution in Propositional and First Order Logic, Deductive
Retrieval, Backward Chaining, Second order Logic. Knowledge Representation: Conceptual
Dependency, Frames, Semantic nets.
Knowledge Based Reasoning: Agents, Facets of Knowledge. Logic and Inferences: Formal Logic,
Propositional and First Order Logic, Resolution in Propositional and First Order Logic, Deductive
Retrieval, Backward Chaining, Second order Logic. Knowledge Representation: Conceptual
Dependency, Frames, Semantic nets.
This is the lecture delivered at Jadavpur University for the engineering students. The lecture was organised by the JU Entrepreneurship Cell and Alumni Association, Singapore Chapter.
1. Dear students get fully solved assignments
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ASSIGNMENT
PROGRAM BSc IT
SEMESTER SIXTH
SUBJECT CODE & NAME BT9402, Artificial Intelligence
CREDIT 4
BK ID B1367
MAX.MARKS 60
Note: Answer all questions. Kindly note that answers for 10 marks questions should be approximately
of 400 words. Each questionis followedbyevaluationscheme.
1 Explainthe first and second principle of AI.
Answer: The field of artificial intelligence, or AI, attempts to understand intelligent entities. Thus, one
reason to studyit is to learn more about ourselves. But unlike philosophy and psychology, which are also
concerned with intelligence, AI strives to build intelligent entities as well as understand them. Another
reason to study AI is that these constructed intelligent entities are interesting and useful in their own
right. AI has produced many significant and impressive products even at this early stage in its
development.Althoughnoone canpredictthe future in
2. 2 Explainknowledge representations withan example.
Answer: Knowledge representation is defined as a problem to solve or a task to carry out, as well as
what constitutes a solution, is only given informally, such as "deliver parcels promptly when they arrive"
or "fix whateveriswrongwiththe electrical systemof the house."
The general framework for solving problems by computer is given in Figure 1.4. To solve a problem,
the designerofa systemmust
Fleshoutthe task and determinewhatconstitutesasolution;
Representthe probleminalanguage withwhichacomputercan reason;
Use the computerto compute anoutput,whichis
3 Explainthe Inheritance and Reificationin semanticnetworks.
Answer: A semantic network, or frame network, is a network which represents semantic relations
between concepts. This is often used as a form of knowledge representation. It is a directed or
undirectedgraphconsistingof vertices,whichrepresentconcepts,andedges.
Reification is the process by which an abstract idea about a computer program is turned into an explicit
data model or other object created in a programming language. A computable/addressable object — a
resource — is created in a system as a proxy for a non computable/addressable object. By means of
reification,somethingthatwaspreviouslyimplicit,
4 Explainthe two principal parts of an expertsystem.
Answer: Expert Systems are computer programs that are derived from a branch of computer science
research called Artificial Intelligence (AI). AI's scientific goal is to understand intelligence by building
computer programs that exhibit intelligent behavior. It is concerned with the concepts and methods of
symbolic inference, or reasoning, by a computer, and how the knowledge used to make those inferences
3. will be represented inside the machine. AI programs that achieve expert-level competence in solving
problemsin taskareasby bringingtobear a body
5 Describe the factors affectinglearningperformance of a system.
Answer: It is important to distinguish between learning (including conditioning) and performance. The
phenomena of cognitive maps and of latent learning both demonstrate that something may be learned
but notshownuntil later.
Factors that influence learning: Several factorsmayaffectlearning.
Learning generally increases with increased amount of practice or training. Practice alone,
however,isnotenough.Classical
6 Brieflyexplainthe hardware requirementsfordesigninga robot.
Answer:Here are the featuresthat robot should be designed:
It shouldbe a vehicle thatcanmove forward,backwardsandturn.
It shouldbe easyto assemble anddisassemble.
It should have a mode in which it is able to move on its own, detecting obstacles ahead and
avoidingthem.
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