Artificial Intelligence 3170716 Syllabus Download

Artificial Intelligence 3170716 Syllabus Download

Artificial Intelligence 3170716 is presented in the 7th semester of the Computer department.

Sr. No.
1 Introduction : The AI Problems, The Underlying Assumption, AI techniques, The Level
of The Model, Criteria For Success
2 Problems, State Space Search & Heuristic Search Techniques: Defining The Problems
As A State Space Search, Production Systems, Production Characteristics, Production
System Characteristics and Issues in the Design of Search Programs, Generate-And-Test,
Hill Climbing, Best-First Search, Problem Reduction, Constraint Satisfaction, Means-Ends
3 Knowledge Representation: Representations And Mappings, Approaches To Knowledge
Representation, Representation Simple Facts In Logic, Representing Instance And Isa
Relationships, Computable Functions and Predicates, Resolution, Procedural versus
Declarative Knowledge, Logic Programming, Forward versus Backward Reasoning
4 Symbolic Reasoning Under Uncertainty: Introduction To Nonmonotonic Reasoning,
Logics For Non-monotonic Reasoning.
5 Probabilistic Reasoning: Probability And Bays’ Theorem, Certainty Factors And RuleBase Systems, Bayesian Networks, Dempster-Shafer Theory, Fuzzy Logic 4
6 Game Playing: Overview, MiniMax Search Procedure, Alpha-Beta Cut-offs,
Refinements, Iterative deepening.
7 Planning: The Blocks World, Components Of a Planning System, Goal Stack Planning,
Nonlinear Planning Using Constraint Posting, Hierarchical Planning, Reactive Systems
8 Natural Language Processing: Introduction, Syntactic Processing, Semantic Analysis,
Discourse And Pragmatic Processing, Spell Checking
9 Connectionist Models: Introduction: Hopfield Network, Learning In Neural Network,
Application Of Neural Networks, Recurrent Networks, Distributed Representations,
Connectionist AI And Symbolic AI.
10 Expert Systems: Representing and Using Domain Knowledge, Expert System Shells,
Explanation, Knowledge Acquisition
11 Genetic Algorithms: A Peek into the Biological World, Genetic Algorithms (GAs),
Significance of the Genetic Operators, Termination Parameters.
12 Introduction to Prolog: Introduction, Converting English to Prolog Facts and Rules,
Goals, Prolog Terminology, Variables, Control Structures, Arithmetic Operators, Matching
in Prolog, Backtracking, Cuts, Recursion, Lists.

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