CS 1032 ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS 3 0 0 100
AIM
To present the concepts of intelligent agents, searching, knowledge and reasoning, planning, learning and expert systems.
OBJECTIVES
i. To study the idea of intelligent agents and search methods.
ii. To study about representing knowledge.
iii. To study the reasoning and decision making in uncertain world.
iv. To construct plans and methods for generating knowledge.
v. To study the concepts of expert systems.
1. INTRODUCTION 9
Introduction to AI: Intelligent agents – Perception –
Natural language processing – Problem – Solving agents – Searching for solutions: Uniformed search strategies – Informed search strategies.
2. KNOWLEDGE AND REASONING 9
Adversarial search – Optimal and imperfect decisions – Alpha, Beta pruning – Logical agents: Propositional logic – First order logic – Syntax and semantics – Using first order logic – Inference in first order logic.
3. UNCERTAIN KNOWLEDGE AND REASONING 8
Uncertainty – Acting under uncertainty – Basic probability notation – Axioms of probability – Baye’s rule – Probabilistic reasoning – Making simple decisions.
4. PLANNING AND LEARNING 9
Planning: Planning problem – Partial order planning – Planning and acting in non-deterministic domains – Learning: Learning decision trees – Knowledge in learning – Neural networks – Reinforcement learning – Passive and active.
5. EXPERT SYSTEMS 10
Definition – Features of an expert system – Organization – Characteristics – Prospector – Knowledge Representation in expert systems – Expert system tools – MYCIN – EMYCIN.
L=45 Total = 45
TEXT BOOKS
1. Stuart Russel and Peter Norvig, ‘Artificial Intelligence A Modern Approach’, Second Edition, Pearson Education, 2003 / PHI.
2. Donald A.Waterman, ‘A Guide to Expert Systems’, Pearson Education.
REFERENCE BOOKS
1. George F.Luger, ‘Artificial Intelligence – Structures and Strategies for Complex Problem Solving’, Fourth Edition, Pearson Education, 2002.
2. Elain Rich and Kevin Knight, ‘Artificial Intelligence’, Second Edition Tata McGraw Hill, 1995.
3. Janakiraman, K.Sarukesi, ‘Foundations of Artificial Intelligence and Expert Systems’, Macmillan Series in Computer Science.
4. W. Patterson, ‘Introduction to Artificial Intelligence and Expert Systems’, Prentice Hall of India, 2003.
AIM
To present the concepts of intelligent agents, searching, knowledge and reasoning, planning, learning and expert systems.
OBJECTIVES
i. To study the idea of intelligent agents and search methods.
ii. To study about representing knowledge.
iii. To study the reasoning and decision making in uncertain world.
iv. To construct plans and methods for generating knowledge.
v. To study the concepts of expert systems.
1. INTRODUCTION 9
Introduction to AI: Intelligent agents – Perception –
Natural language processing – Problem – Solving agents – Searching for solutions: Uniformed search strategies – Informed search strategies.
2. KNOWLEDGE AND REASONING 9
Adversarial search – Optimal and imperfect decisions – Alpha, Beta pruning – Logical agents: Propositional logic – First order logic – Syntax and semantics – Using first order logic – Inference in first order logic.
3. UNCERTAIN KNOWLEDGE AND REASONING 8
Uncertainty – Acting under uncertainty – Basic probability notation – Axioms of probability – Baye’s rule – Probabilistic reasoning – Making simple decisions.
4. PLANNING AND LEARNING 9
Planning: Planning problem – Partial order planning – Planning and acting in non-deterministic domains – Learning: Learning decision trees – Knowledge in learning – Neural networks – Reinforcement learning – Passive and active.
5. EXPERT SYSTEMS 10
Definition – Features of an expert system – Organization – Characteristics – Prospector – Knowledge Representation in expert systems – Expert system tools – MYCIN – EMYCIN.
L=45 Total = 45
TEXT BOOKS
1. Stuart Russel and Peter Norvig, ‘Artificial Intelligence A Modern Approach’, Second Edition, Pearson Education, 2003 / PHI.
2. Donald A.Waterman, ‘A Guide to Expert Systems’, Pearson Education.
REFERENCE BOOKS
1. George F.Luger, ‘Artificial Intelligence – Structures and Strategies for Complex Problem Solving’, Fourth Edition, Pearson Education, 2002.
2. Elain Rich and Kevin Knight, ‘Artificial Intelligence’, Second Edition Tata McGraw Hill, 1995.
3. Janakiraman, K.Sarukesi, ‘Foundations of Artificial Intelligence and Expert Systems’, Macmillan Series in Computer Science.
4. W. Patterson, ‘Introduction to Artificial Intelligence and Expert Systems’, Prentice Hall of India, 2003.
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