IT8601 – NOTES & QP
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| SEMESTER QP | CLICK HERE |
IT8601 – SYLLABUS
UNIT I INTRODUCTION
Introduction to Artificial Intelligence-Search-Heuristic Search-A* algorithm-Game Playing- Alpha-Beta Pruning-Expert systems-Inference-Rules-Forward Chaining and Backward Chaining- Genetic Algorithms.
UNIT II KNOWLEDGE REPRESENTATION AND REASONING
Proposition Logic — First Order Predicate Logic — Unification — Forward Chaining -Backward Chaining — Resolution — Knowledge Representation — Ontological Engineering — Categories and Objects — Events — Mental Events and Mental Objects — Reasoning Systems for Categories — Reasoning with Default Information — Prolog Programming.
UNIT III UNCERTAINTY
Non monotonic reasoning-Fuzzy Logic-Fuzzy rules-fuzzy inference-Temporal Logic-Temporal Reasoning-Neural Networks-Neuro-fuzzy Inference.
UNIT IV LEARNING
Probability basics — Bayes Rule and its Applications — Bayesian Networks — Exact and Approximate Inference in Bayesian Networks — Hidden Markov Models — Forms of Learning — Supervised Learning — Learning Decision Trees — Regression and Classification with Linear Models — Artificial Neural Networks — Nonparametric Models — Support Vector Machines — Statistical Learning — Learning with
Complete Data — Learning with Hidden Variables- The EM Algorithm — Reinforcement Learning
UNIT V INTELLIGENCE AND APPLICATIONS
Natural language processing-Morphological Analysis-Syntax analysis-Semantic Analysis-AIl applications — Language Models — Information Retrieval — Information Extraction — Machine Translation — Machine Learning — Symbol-Based — Machine Learning: Connectionist — Machine Learning.