ARTIFICIAL INTELLIGENCE AND NEURAL NETWORKS

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.


wumpus world game 

All Figures in the textbook 1


 bayes-nets.pdf          27-Dec-2006 10:55   95K  
[   ] fopc.4.pdf 25-Dec-2006 15:26 16K
[   ] games.4.pdf 25-Dec-2006 15:25 68K
[   ] heuristic-search.4.pdf 25-Dec-2006 15:25 31K
[   ] inference-sys.4.pdf 25-Dec-2006 15:26 24K
[   ] inference.4.pdf 25-Dec-2006 15:26 46K
[   ] intro.4.pdf 25-Dec-2006 15:25 14K
[   ] learning.pdf 20-Apr-2009 18:20 83K
[   ] logic.4.pdf 25-Dec-2006 15:25 20K
[   ] neural.pdf 27-Dec-2006 15:47 109K
[   ] nlp.pdf 04-May-2009 15:17 529K
[   ] old-nlp.pdf 25-Apr-2009 15:43 8.5K
[   ] philosophy.4.pdf 25-Dec-2006 16:28 18K
[   ] planning.4.pdf 25-Dec-2006 15:46 25K
[   ] pop.4.pdf 25-Dec-2006 15:47 26K
[   ] probability.pdf 20-Apr-2009 18:20 93K
[   ] search.4.pdf 25-Dec-2006 15:25 37K
[   ] state-of-art.pdf 15-Jan-2007 09:13 4.2K
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saikishor jangiti,
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saikishor jangiti,
Jan 4, 2011, 8:24 AM
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