7400 TTL

ARTIFICIAL INTELLIGENCE
EE-705B
Credit: 3
 

 

Introduction:
Intelligent Agents – Agents and environments - Good behavior – The nature of
environments – structure of agents - Problem Solving - problem solving agents – example
problems – searching for solutions – uniformed search strategies - avoiding repeated states –
searching with partial information.
Searching techniques:
Informed search and exploration – Informed search strategies – heuristic function – local
search algorithms and optimistic problems – local search in continuous spaces – online
search agents and unknown environments - Constraint satisfaction problems (CSP) –
Backtracking search and Local search for CSP – Structure of problems - Adversarial Search –
Games – Optimal decisions in games – Alpha – Beta Pruning – imperfect real-time decision
– games that include an element of chance.
Knowledge representation:
First order logic – representation revisited – Syntax and semantics for first order logic – Using
first order logic – Knowledge engineering in first order logic - Inference in First order logic –
prepositional versus first order logic – unification and lifting – forward chaining – backward
chaining - Resolution - Knowledge representation - Ontological Engineering - Categories and
objects – Actions - Simulation and events - Mental events and mental objects.
Learning:
Learning from observations - forms of learning - Inductive learning - Learning decision trees
- Ensemble learning - Knowledge in learning – Logical formulation of learning – Explanation
based learning – Learning using relevant information – Inductive logic programming -
Statistical learning methods - Learning with complete data - Learning with hidden variable -
EM algorithm - Instance based learning - Neural networks - Reinforcement learning –
Passive reinforcement learning - Active reinforcement learning - Generalization in
reinforcement learning.
Applications:
Communication – Communication as action – Formal grammar for a fragment of English –
Syntactic analysis – Augmented grammars – Semantic interpretation – Ambiguity and
disambiguation – Discourse understanding – Grammar induction - Probabilistic language
processing - Probabilistic language models – Information retrieval – Information Extraction
– Machine translation.
 

 

Text Books:
1. Artificial Intelligence – A Modern Approach”, Stuart Russell, Peter Norvig, 2nd Edition, Pearson Education /
Prentice Hall of India, 2004.
Reference Books:
1. Artificial Intelligence: A new Synthesis, Nilsson. J. Nils , Harcourt Asia Pvt. Ltd., 2000.
2. Artificial Intelligence, Rich Elaine & Knight Kevin, 2nd Edition, Tata McGraw-Hill, 2003.
3. Artificial Intelligence-Structures and Strategies for Complex Problem Solving, Geogre