Artificial Intelligence III

Overview For an autonomous agent to behave in an intelligent manner it must be able to solve problems. This means it should be able to arrive at decisions that transform a given situation into a desired or goal situation. The agent should be able to imagine the consequence of its decisions to be able to identify the ones that work. In this first course on AI we study a wide variety of search methods that agents can employ for problem solving.

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Created by skill expert
Last updated Sat, 18-Jun-2022
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Course overview
Lecture Details

Artificial Intelligence by Prof. Deepak Khemani,Department of Computer Science and Engineering,IIT Madras.For more details on NPTEL visit httpnptel.ac.in

Course Details

COURSE LAYOUT

Week 1: Introduction: Overview and Historical Perspective, Turing Test, Physical Symbol Systems and the scope of Symbolic AI, Agents.
Week 2: State Space Search: Depth First Search, Breadth First Search, DFID
Week 3: Heuristic Search: Best First Search, Hill Climbing, Beam Search
Week 4: Traveling Salesman Problem, Tabu Search, Simulated Annealing
Week 5: Population Based Search: Genetic Algorithms, Ant Colony Optimization
Week 6: Branch & Bound, Algorithm A*, Admissibility of A*
Week 7: Monotone Condition, IDA*, RBFS, Pruning OPEN and CLOSED in A*
Week 8: Problem Decomposition, Algorithm AO*, Game Playing
Week 9: Game Playing: Algorithms Minimax, AlphaBeta, SSS*
Week 10: Rule Based Expert Systems, Inference Engine, Rete Algorithm
Week 11: Planning: Forward/Backward Search, Goal Stack Planning, Sussmans Anomaly
Week 12: Plan Space Planning, Algorithm Graphplan

The following topics are not part of evaluation for this course, and are included for the interested student. These topics will be covered in detail in two followup courses "AI: Knowledge Representation and Reasoning" and "AI: Constraint Satisfaction Problems".

A1 Constraint Satisfaction Problems, Algorithm AC-1, Knowledge Based Systems
A2 Propositional Logic, Resolution Refutation Method
A3 Reasoning in First Order Logic, Backward Chaining, Resolution Method
Curriculum for this course
48 Lessons 39:24:27 Hours
Lecture
48 Lessons 39:24:27 Hours
  • Artificial Intelligence Introduction
    Preview 00:56:03
  • Introduction to AI
    00:51:55
  • AI Introduction Philosophy
    00:44:11
  • AI Introduction I
    00:53:18
  • Introduction Philosophy
    00:35:12
  • State Space Search Intro
    00:54:03
  • Search-DFS and BFS
    00:54:11
  • Search DFID
    00:51:10
  • Heuristic Search
    00:55:49
  • Hill Climbing
    00:44:28
  • Solution Space Search,Beam Search
    00:42:40
  • TSP Greedy Methods
    00:52:26
  • Tabu Search
    00:38:18
  • Optimization I (Simulated Annealing)
    00:48:13
  • Optimization II (Genetic Algorithms)
    00:53:39
  • Population Based Methods for Optimization
    00:51:07
  • Population Based Methods II
    00:58:25
  • Branch and Bound,Dijkstras Algorithm
    00:56:07
  • A Algorithm
    00:49:31
  • Admissibility of A
    00:51:22
  • A Monotone Property,Iteractive Deeping A
    00:46:31
  • Recursive Best First Search,Sequence Allignment
    00:49:46
  • Pruning the Open and Closed Lists
    00:50:24
  • Problem Decomposition with goal Trees
    00:48:11
  • AO Algorithm
    00:47:02
  • Game Playing
    00:44:07
  • Game Playing Minimax Search
    00:45:59
  • Game Playing AlphaBeta
    00:47:46
  • Game Playing SSS I
    00:50:13
  • Rule Based Systems
    00:47:32
  • Inference Engines
    00:41:09
  • Rete Algorithm
    00:49:27
  • Planning
    00:50:23
  • Planning FSSP,BSSP
    00:53:30
  • Goal Stack Planning Sussmans Anomaly
    00:50:10
  • Non Linear Planning
    00:45:54
  • Plan Space Planning
    00:50:50
  • Graph Plan
    00:47:49
  • Constraint Satisfaction Problems
    00:52:00
  • CSP Continued
    00:49:24
  • Knowlege Based Systems
    00:53:20
  • Knowledge Based Systems PL I
    00:49:38
  • Propositional Logic
    00:48:56
  • Resolution Refutation for PL
    00:40:59
  • First Order Logic (FOL)
    00:52:45
  • Reasoning in FOL
    00:49:18
  • Backward Chaining
    00:53:10
  • Resolution for FOL
    00:46:06
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