SCHEME/SYLLABUS : MCA(SE)
(Fourth Semester)

Code No: IT 712
Paper : Artificial Intelligence

Scope of AI
Games, theorem proving, natural language processing, vision and speech processing, robotics, expert systems, AI techniques- search knowledge, abstraction.

Problem solving
State space search; Production systems, search space control: depth-first, breadth-first search, heuristic search - Hill climbing, best-first search, branch and bound. Problem Reduction, Constraint Satisfaction End, Means-End Analysis

Knowledge Representation
Predicate Logic: Unification, modus pones, resolution, dependency directed backtracking.Rule based Systems : Forward reasoning: conflict resolution, backward reasoning: use of no backtrack.

Structured Knowledge Representation: Semantic Nets: slots, exceptions and default frames, conceptual dependency, scripts.

Handling uncertainty
Non-Monotonic Reasoning, Probablistic reasoning, use of certainty factors, fuzzy logic.

Learning
Concept of learning, learning automation, genetic algorithm, learning by inductions, neural nets.

Expert Systems
Need and justification for expert systems, knowledge acquisition, Case studies: MYCIN, RI.

Text:

1. E. Rich and K. Knight, “Artificial intelligence”, TMH, 2nd ed., 1992.
2. N.J. Nilsson, “Principles of AI”, Narosa Publ. House, 1990.

Reference:

1. D.W. Patterson, “Introduction to AI and Expert Systems”, PHI, 1992.
2. Peter Jackson, “Introduction to Expert Systems”, AWP, M.A., 1992.
3. R.J. Schalkoff, “Artificial Intelligence - an Engineering Approach”, McGraw Hill Int Ed., Singapore, 1992.
4. M. Sasikumar, S. Ramani, “Rule Based Expert Systems”, Narosa Publishing House, 1994.

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