Prolog is a declarative logic programming language where programs consist of facts and rules. Facts are terms that are always true, while rules define relationships between terms using implication. A knowledge base can be queried by asking questions, and Prolog will attempt to prove queries using the facts and rules. Prolog is commonly used for artificial intelligence applications such as natural language processing, knowledge representation, and automated reasoning.
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Fundamentals of Artificial Intelligence Introduction, A.I. Representation, Non-AI & AI Techniques, Representation of Knowledge, Knowledge Base Systems, State Space Search, Production Systems, Problem Characteristics, types of production systems, Intelligent Agents and Environments, concept of rationality, the nature of environments, structure of agents, problem solving agents, problem formulation ,Searching Planning Blocks world, STRIPS, Implementation using goal stack, Partial Order Planning, Hierarchical planning, and least commitment strategy. Conditional Planning, Continuous Planning Machine Learning AlgorithmsKnowledge Representation Knowledge based agents, Wumpus world, Propositional Logic: Representation, Inference, Reasoning Patterns, Resolution, First order Logic: Representation, Inference, Reasoning Patterns, Resolution, Forward and Backward Chaining. Basics of PROLOG: Representation, Structure, Backtracking, Expert System. Uncertainty Non Monotonic Reasoning, Logics for Non Monotonic Reasoning, Forward rules and Backward rules, Justification based Truth Maintenance Systems, Semantic Nets Statistical Reasoning, Probability and Bayes’ theorem, Bayesian Network, Markov Networks, Hidden Markov Model, Basis of Utility Theory, Utility Functions.
This presentation contains my one day lectures which introduces fuzzy set theory, operations on fuzzy sets, some engineering control applications using Mamdamn model.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
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Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
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This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
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UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
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Why are attacks on smart factories rising?
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https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
2. Outline
• What is Prolog?
• Prolog basics
• Prolog Demo
• Syntax:
– Atoms and Variables
– Complex Terms
– Facts & Queries
– Rules
• Examples
3. What is Prolog?
• Prolog is the most commonly used logic
– Simple syntax
• PROgramming in LOGic
• High-level interactive language.
• Logic programming language.
4. What is Prolog? (Cont.)
• Programming languages are of two kinds:
– Procedural (BASIC, Pascal, C++, Java);
– Declarative (LISP, Prolog, ML).
• In procedural programming, we tell the computer how
to solve a problem.
• In declarative programming, we tell the computer what
problem we want solved.
• (However, in Prolog, we are often forced to give clues
as to the solution method).
5. The use of Prolog
• Prolog is used in artificial intelligence applications such as:
– Natural language interfaces,
– automated reasoning systems and
– Expert systems: usually consist of a data base of facts and
rules and an inference engine, the run time system of Prolog
provides much of the services of an inference engine.
6. What is Prolog used for?
• Good at
– Grammars and Language processing,
– Knowledge representation and reasoning,
– Unification,
– Pattern matching,
– Planning and Search.
• Poor at:
– Repetitive number crunching,
– Representing complex data structures,
– Input/Output (interfaces).
7. Basic Elements of Prolog
• A program consists of clauses. These are of 3 types: facts, rules,
and questions (Queries).
• Some are always true (facts):
father( ali, haya).
• Some are dependent on others being true (rules):
parent( Person1, Person2 ) :- father( Person1, Person2 ).
• To run a program, we ask questions about the database.
KB
Prolog
Interpreter
Query
Answer
8. Prolog in English• Example Database:
– Saleh is a teacher
– Nora is a teacher
– Saleh is the father of Jaber.
– Nora is the mother of Jaber.
– Hamza is the father of Saleh
– Person 1 is a parent of Person 2 if
Person 1 is the father of Person 2 or
Person 1 is the mother of Person 2.
– Person 1 is a grandparent of Person 2 if
some Person 3 is a parent of Person 2 and
Person 1 is a parent of Person 3.
• Example questions:
– Who is Jaber's father?
– Is Nora the mother of Jaber?
– Does Hamza have a grandchild?
Facts
Rules
9. A knowledge base of facts
• teacher(saleh).
• teacher(nora).
• father( saleh, jaber).
• mother( nora, jaber ).
• father( hamza, saleh ).
Queries we can ask
?- teacher(saleh). Yes
?- teacher(nora). Yes
?- mother( nora, jaber ). Yes
?- mother( nora, saleh ). No
?- grandparent( hamza, X). Jaber
?- nurse(nora).
ERROR: Undefined procedure: nurse/1
10. More queries we can ask
• ?-teacher(X).
– X=saleh ;
– X=nora ;
– No.
• ?-mother(X,Y).
– X = nora
– Y = jaber ;
– No
11. Syntax: Atoms and Variables
• Atoms:
– All terms that consist of letters, numbers, and the underscore
and start with a non-capital letter are atoms: uncle_ali, nora,
year2007, . . . .
– All terms that are enclosed in single quotes are atoms:
’Aunt Hiba’, ’(@ *+ ’, . . . .
– Certain special symbols are also atoms: +, ,, . . . .
• Variables:
– All terms that consist of letters, numbers, and the underscore
and start with a capital letter or an underscore are variables:
X, Jaber, Lama, . . . .
– _is an anonymous variable: two occurrences of _are different
variables.
– E.g. if we are interested in people who have children, but not
in the name of the children, then we can simply ask: ?-
parent(X,_).
12. Syntax: Complex Terms
• Complex terms
– Complex terms are of the form:
functor (argument, ..., argument).
– Functors have to be atoms.
– Arguments can be any kind of Prolog term, e.g., complex
terms.
• likes(lama,apples), likes(amy,X).
13. Syntax: Facts & Queries
• Facts are complex terms which begin with lower case alphabetic
letter and ends with a full stop.
– teacher(nora).
– female( aunt hiba).
– likes(alia,choclate).
• Queries are also complex terms followed by a full stop.
– ?- teacher(nora).
Query
Prompt provided by the Prolog interpreter.
14. Syntax: Rules
• A Prolog rule consists of a head and a body.
a(X) :- b(X), c(X)
• Rules are of the form Head :- Body.
• Like facts and queries, they have to be followed by a full stop.
• Head is a complex term.
• Body is complex term or a sequence of complex terms separated by
commas.
happy(uncle_ yussef) :- happy(nora).
grandparent( Person1, Person2 ) :- parent( Person3, Person2 ) ,
parent( Person1, Person3 ).
head body
15. A knowledge base of facts & Rules
• happy(uncle_ yussef) :- happy(nora).
if ... then ...: If happy(nora) is true, then happy(uncle_ yussef) is true.
• parent( Person1, Person2 ) :- father( Person1, Person2 ).
• parent( Person1, Person2 ) :- mother( Person1, Person2 ).
Person 1 is a parent of Person 2 if Person 1 is the father of Person 2
or Person 1 is the mother of Person 2.
• grandparent( Person1, Person2 ) :- parent( Person3, Person2 )
, parent( Person1, Person3 ).
Person 1 is a grandparent of Person 2 if some Person 3 is a parent of Person 2
and Person 1 is a parent of Person 3.
16. Querying slide 15
• ?- happy(nora). Yes
• ?-happy(uncle_yussef). yes
• ?- happy(X).
– X = uncle_yussef ;
– X = nora ;
– No
• Does Hamza have a grandchild?
• ?- grandparent(hamza,_).
– Yes
17. Facts & Rules containing variables
• teacher(saleh).
• teacher(nora).
• father( saleh, jaber).
• mother( nora, jaber ).
• This knowledge base defines 3 predicates:
– teacher/1.
– father/2, and
– mother/2.
• teacher(X) :- father(Y,X), teacher(Y),mother(Z,X), teacher(Z).
• For all X, Y, Z, if father(Y,X)is true and teacher (Y) is true and
mother(Z,X) is true and teacher (Z) is true, then teacher (X) is true.
• I.e., for all X, if X’s father and mother are teachers,
then X is a teacher.
18. Summary
• A Prolog program consists of a database of facts and rules, and
queries (questions).
– Fact: ... .
– Rule: ... :- ... .
– Query: ?- ... .
– Variables: must begin with an upper case letter or underscore.
• Nora, _nora.
– Constants (atoms): begin with lowercase letter, or enclosed in
single quotes.
• uncle_ali, nora, year2007, .
• numbers 3, 6, 2957, 8.34, ...
– complex terms An atom (the functor) is followed by a comma
separated sequence of Prolog terms enclosed in parenthesis (the
arguments).
• likes(lama,apples), likes(amy,X).