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||Search: Problem representation; State Space Search; A* Algorithm and its Properties; AO* search, Minimax and alpha-beta pruning, AI in games.
Logic: Formal Systems; Notion of Proof, Decidability, Soundness, Consistency and Completeness; Predicate Calculus (PC), Resolution Refutation, Herbrand Interpretation, Prolog.
Knowledge Representation: PC based Knowledge Representation, Intelligent Question Answering, Semantic Net, Frames, Script, Conceptual Dependency, Ontologies, Basics of Semantic Web.
Leaning: Learning from Examples, Decision Trees, Neural Nets, Hidden Markov Models, Reinforcement Learning, Learnability Theory.
Uncertainty: Formal and Empirical approaches including Bayesian Theory, Fuzzy Logic, Non-monotonic Logic, Default Reasoning.
Planning: Blocks World, STRIPS, Constraint Satisfaction, Basics of Probabilistic Planning.
Advanced Topics: Introduction to topics like Computer Vision, Expert Systems, Natural Language Processing, Big data, Neuro Computing, Robotics, Web Search.