SEMESTER VI CS1351 – ARTIFICIAL INTELLIGENCE Syllabus

ANNA UNIVERSITY TIRUCHIRAPPALLI
Tiruchirappalli - 620 024
Regulations 2007
Syllabus
SEMESTER VI

CS1351 – ARTIFICIAL INTELLIGENCE

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UNIT I AGENTS AND SEARCHING 8
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.

UNIT II SEARCHING TECHNIQUES 10
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.

UNIT III KNOWLEDGE REPRESENTATION 10
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.

UNIT IV LEARNING 9
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.

UNIT V APPLICATIONS 8
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.

Total: 45
TEXT BOOK
1. Russell, S. and Norvig, P., “Artificial Intelligence-A Modern Approach”, 2nd Edition, Pearson
Education / Prentice Hall of India, 2004.

REFERENCES
1. Nilsson, N.J., “Artificial Intelligence: A new Synthesis”, Harcourt Asia Pvt. Ltd., 2000.
2. Elaine Rich and Kevin Knight, “Artificial Intelligence”, 2nd Edition, Tata McGraw-Hill, 2003.
3. Luger, G.F., “Artificial Intelligence − Structures and Strategies for Complex Problem Solving”,
Pearson Education / Prentice Hall of India, 2002.

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