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Artificial Intelligence

  •  Lessons 10
  •  No. of Downloads 876
  •  Course Type Post Graduate
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Foundation and history of artificial intelligent, problems and techniques – AI programming languages, introduction to LISP and PROLOG

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Problem spaces and searches, blind search strategies, Breadth first- Depth first search - heuristic search techniques

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Heuristic search techniques Hill climbing: best first-A* algorithm AO* algorithm

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Knowledge representation issues, predicate logic- logic programming, semantic nets- frames and inheritance

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Constraint propagation, representing knowledge using rules, rules based deduction systems.

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Reasoning under uncertainty, review of probability, symbolic reasoning under uncertainty, Statistical reasoning, Fuzzy reasoning, Temporal reasoning, Non-monotonic reasoning.

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AI application to robotics, and current trends in intelligent systems

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Principles of Natural language processing, rule based systems architecture

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Learning from examples, discovery as learning, learning by analogy, explanation based learning, neural nets, genetic algorithms.

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Planning and planning in situational calculus, representation for planning, partial order planning algorithm,

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