Artificial Intelligence

Artificial Intelligence Training propvided by university Indian Institute of Technology Madras

Beginner 0(0 Ratings) 0 Students enrolled
Created by IIT Madras Staff Last updated Wed, 02-Mar-2022 English


Artificial Intelligence free videos and free material uploaded by Indian Institute of Technology, chennai (IIT chennai). This session contains about Artificial Intelligence Updated syllabus , Lecture notes , videos , MCQ , Privious Question papers and Toppers Training Provided Training of this course. If Material not uploaded check another subject

Syllabus / What will i learn?

Artificial Intelligence: Introduction.
Introduction to AI.
AI Introduction: Philosophy.
AI Introduction.
Introduction: Philosophy.
State Space Search - Introduction.
Search - DFS and BFS.
Search DFID.
Heuristic Search.
Hill climbing.
Solution Space Search,Beam Search.
TSP Greedy Methods.
Tabu Search.
Optimization - I (Simulated Annealing).
Optimization II (Genetic Algorithms).
Population based methods for Optimization.
Population Based Methods II.
Branch and Bound, Dijkstra's Algorithm.
A* Algorithm.
Admissibility of A*.
A* Monotone Property, Iterative Deeping A*.
Recursive Best First Search, Sequence Allignment.
Pruning the Open and Closed lists.
Problem Decomposition with Goal Trees.
AO* Algorithm.
Game Playing.
Game Playing- Minimax Search.
Game Playing - AlphaBeta.



48 Resolution for FOL.



Curriculum for this course
0 Lessons 00:00:00 Hours
+ View more
Description

Instructor: Prof. Deepak Khemani, Department of Computer Science and Engineering, IIT Madras.

This course provides an introduction to artificial intelligence. Topics include Introduction: Overview and Historical Perspective, Turing test, Physical Symbol Systems and the scope of Symbolic AI, Agents; State Space Search: Depth First Search, Breadth-First Search, DFID; Heuristic Search: Best First Search, Hill Climbing, Beam Search, Tabu Search; Randomized Search: Simulated Annealing, Genetic Algorithms, Ant Colony Optimization; Finding Optimal Paths: Branch and Bound, A*, IDA*, Divide and Conquer approaches, Beam Stack Search; Problem Decomposition: Goal Trees, AO*, Rule-Based Systems, Rete Net; Game Playing: Minimax Algorithm, Alpha-Beta Algorithm, SSS*; Planning and Constraint Satisfaction: Domains, Forward and Backward Search, Goal Stack Planning, Plan Space Planning, Graphplan, Constraint Propagation; Logic and Inferences: Propositional Logic, First Order Logic, Soundness and Completeness, Forward and Backward chaining.

You need online training / explanation for this course?
1:1 Online Training / Explanation Fee: 1 /- Month

1 to 1 Online Training contact instructor for demo :


+ View more

Other related courses
Updated Wed, 22-Apr-2020
26 Lessons
5 Free
Updated Wed, 22-Apr-2020
11 Lessons
0 Free
Updated Wed, 22-Apr-2020
29 Lessons
0 Free
Updated Sun, 20-Sep-2020
24 Lessons
0 ₹ 199
Updated Wed, 24-Feb-2021
35 Lessons
0 Free
Updated Wed, 22-Apr-2020
20 Lessons
0 Free
Updated Wed, 22-Apr-2020
38 Lessons
0 Free
Updated Thu, 30-Apr-2020
10 Lessons
0 Free
Updated Thu, 30-Apr-2020
43 Lessons
0 Free
About the instructor
  • 0 Reviews
  • 5 Students
  • 330 Courses
+ View more
Student feedback
0
Average rating
  • 0%
  • 0%
  • 0%
  • 0%
  • 0%
Reviews

Material price :

Free

1:1 Online Training Fee: 1 /- Month
Contact instructor for demo :