WITH EFFECT FROM THE ACADEMIC YEAR 2013–2014
CS402
ARTIFICIAL INTELLIGENCE
Instruction 4 Periods per week
Duration of University Examination 3 Hours
University Examination 75 Marks
Sessional 25 Marks
UNIT-I
Introduction: Definition, history and applications of AI. Search in State Spaces: Agents that plan, Uninformed search, Algorithm A*, Heuristic Functions and Search Efficiency, Alternative Search Formulations and Applications, Adversarial Search.
UNIT – II
Knowledge Representation and Reasoning: The Propositional Calculus, Resolution in Propositional Calculus, The Predicate Calculus, Resolution in Predicate Calculus, Rule-Based Expert Systems, Representing Common Sense Knowledge.
UNIT-III
Reasoning with Uncertain Information: Review of probability theory, Probabilistic Inference, Bayes Networks.
Planning Methods Based on Logic: The Situation Calculus, Planning.
UNIT-IV
Learning from Observations: Learning decision-trees using Information theory, Learning General Logical Descriptions, Neural Networks: Perceptron, Multilayer feed-forward neural network. Rule Learning.
UNIT-V
Natural Language Processing: Communication among agents
Fuzzy Logic Systems: Crisp Sets, Fuzzy Sets, Some fuzzy terminology, Fuzzy Logic Control, Sugeno Style of Fuzzy inference processing, Fuzzy hedges, Cut Threshold, Neuro Fuzzy systems.
Suggested Reading:
- Nils J. Nilsson (1998) Artificial Intelligence: A New Synthesis, Elsevier
- Stuart Russell, Peter Norvig (1995), Artificial Intelligence – A Modern Approach, Pearson Edition/PHI.
- Elaine Rich, Kevin Knight, Shivashankar B Nair (2009), Artificial Intelligence, Third edition, Tata McGraw Hill.
References :
- George F Luger (2009), Artificial Intelligence, Structures and strategies for Complex Problem solving, Pearson Edition.