Study videos of Artificial Intelligence and Neural Networks

Download/Source url :

http://www.youtube.com/watch?v=eLbMPyrw4rw&feature=player_embedded

By Prof. P. Dasgupta, Department of Computer Science & Engineering, I.I.T,kharagpur.


ARTIFICIAL INTELLIGENCE AND NEURAL NETWORKS SYLLABUS :

Source :http://jntuk.edu.in

UNIT - I
Introduction : AI problems, foundation of AI and history of AI intelligent agents: Agents and
Environments,the concept of rationality, the nature of environments, structure of agents, problem solving
agents, problemformulation.


UNIT - II
Searching : Searching for solutions, uniformed search strategies – Breadth first search, depth first
Search. Search with partial information (Heuristic search) Greedy best first search, A* search Game
Playing: Adversial search, Games, minimax, algorithm, optimal decisions in multiplayer games, Alpha-
Beta pruning, Evaluation functions, cutting of search.


UNIT - III
Knowledge Representation & Reasons logical Agents, Knowledge – Based Agents, the Wumpus world,
logic, propositional logic, Resolution patterns in propos ional logic, Resolution, Forward & Backward.
Chaining.


UNIT - IV
First order logic. Inference in first order logic, propositional Vs. first order inference, unification & lifts
forward chaining, Backward chaining, Resolution.


UNIT - V
Characteristics of Neural Networks, Historical Development of Neural Networks Principles, Artificial
Neural Networks: Terminology, Models of Neuron, Topology, Basic Learning Laws, Pattern Recognition
Problem, Basic Functional Units, Pattern Recognition Tasks by the Functional Units.


UNIT - VI
Feedforward Neural Networks:
Introduction, Analysis of pattern Association Networks, Analysis of Pattern Classification Networks,
Analysis of pattern storage Networks. Analysis of Pattern Mapping Networks.


UNIT - VII
Feedback Neural Networks
Introduction, Analysis of Linear Autoassociative FF Networks, Analysis of Pattern Storage Networks.


UNIT - VIII
Competitive Learning Neural Networks & Complex pattern Recognition
Introduction, Analysis of Pattern Clustering Networks, Analysis of Feature
Mapping Networks, Associative Memory.


TEXT BOOKS :
1. Artificial Intelligence – A Modern Approach. Second Edition, Stuart Russel, Peter Norvig, PHI/ Pearson
Education.
2. Artificial Neural Networks B. Yagna Narayana, PHI


REFERENCES :
1. Artificial Intelligence , 2nd Edition, E.Rich and K.Knight (TMH).
2. Artificial Intelligence and Expert Systems – Patterson PHI.
3. Expert Systems: Principles and Programming- Fourth Edn, Giarrantana/ Riley, Thomson.
4. PROLOG Programming for Artificial Intelligence. Ivan Bratka- Third Edition – Pearson Education.
5.Neural Networks Simon Haykin PHI
6. Artificial Intelligence, 3rd Edition, Patrick Henry Winston., Pearson Edition.

6:27 PM