CSVTU BE VII Semester ET&T Artificial Intelligence & Expert System Syllabus

Chhattisgarh Swami Vivekanand Technical University, Bhilai

Semester : VII Branch: Electronics & Telecommunication

Subject: Artificial Intelligence & Expert System

Total Theory Periods: 40 Total Tutorial Periods: 12

Total Marks in End Semester Examination: 80

Minimum number of Class tests to be conducted: Two

UNIT – I

Overview of AI :

 

What is AI? The importance of AI, Early works in AI, AI and Related fields. Knowledge:

Importance of Knowledge, knowledge-based system representation, organization, manipulation, acquisition.

 

UNIT – II

Search Techniques:

 

Problem Solving, State space search, Blind search: Depth first search, Breadth first

search, informed search: Heuristic search, Hill climbing search, Best first search, A*, AO*, Constraint

 

satisfaction. Game Playing: Minimax search, Alpha – beta pruning.

 

UNIT – III

Knowledge Representation:

 

Predicate Logic ( well formed formulas, quantifiers, Prenex Normal Form,

Skolemization , Unification, Modus pones, Resolution refutation – various strategies ), Rule Based Systems (

 

Forward reasoning: Conflict resolution , Conflict resolution, backward reasoning: Use of No. Backtracking,

 

Structured Knowledge Representations (Semantic Net: slots, inheritance, Frames: exceptions and defaults

 

handling. Conceptual Dependency formalism, Object oriented representations.

 

UNIT – IV

Handling uncertainty:

 

Probabilistic reasoning: Bayes Net, Dempster Shafer Theory, Use of certainty Factors,

Fuzzy Logic, Non monotonic reasoning, Dependency directed backtracking, Truth maintenance systems,

 

Learning : Concept of learning, Learning automation, The Genetic algorithm, Learning by induction, Neural

 

Networks: Hopfield Networks, Perceptrons- Learning algorithm, Back propagation Network, Boltzman

 

Machine, Recurrent Networks.

 

UNIT – V

Planning:

 

Components of Planning System, Plan Generation Algorithms: Forward state propagation,

Backward state propagation, Nonlinear planning using constraint posting, Natural Language Processing:

 

Syntactic analysis, Top down and bottom up parsing, Augmented Transition Networks, Semantic analysis,

 

case grammars.

 

Expert System:

 

Need and Justification for expert systems- cognitive problems, Expert System Architectures(

Rule based systems, Non production system, knowledge acquisition, Case studies: MYCIN , R1.

 

Name of Text Books:

1. Artificial Intelligence By Elaine Rich and Kevin Knight , Tata McGraw Hill.

2. Introduction to AI and Expert Systems By Dan W.Patterson, PHI.

Name of Reference Books:

1. Principles of Artificial Intelligence By Nils J.Nilsson, Narosa Pub. house.

2. Foundation Artificial Intelligence & Expe

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