Artificial intelligence (AI), is also called as machine intelligence. It is a branch of computer science which demonstrated by Artificial Intelligence machines, unlike the natural intelligence. It has capability to analyze its environment using either predetermined rules and search algorithms, or pattern recognizing machine learning models.For instance: speech recognition, problem-solving, learning and planning etc.
Approaches to AI: Turing Test and Rational Agent Approaches; State Space Representation of Problems, Heuristic Search Techniques, Game Playing, Min-Max Search, Alpha Beta Cutoff Procedures. Knowledge Representation: Logic, Semantic Networks, Frames, Rules, Scripts, Conceptual Dependency and Ontologies; Expert Systems, Handling Uncertainty in Knowledge. Planning: Components of a Planning System, Linear and Non Linear Planning; Goal Stack Planning, Hierarchical Planning, STRIPS, Paltial Order Planning. Natural Language Processing: Grammar and Language; Parsing Techniques, Semantic Analysis and Prgamatics. Multi Agent Systems: Agents and Objects; Agents and Expert Systems; Genetic Structure of Multiagent System, Semantic Web, Agent Conummication, Knowledge Sharing using
Ontologies, Agent Development Tools. Fuzzy Sets: Notion of Fuzziness, Membership Functions, Fuzzification and Defuzzification; Operations on Fuzzy Sets, Fuzzy Functions and Linguistic Valiables; Fuzzy Relations, Fuzzy Rules and Fuzzy Inference; Fuzzy Control System and Fuzzy Rule Based Systems. Genetic Algorithms (GA): Encoding Strategies, Genetic Operators, Fitness Functions and GA Cycle; Problem Solving using GA. Artificiai Neural Networks (ANN): Supelvised, Unsupelvised and Reinforcement Leaming; Single Perceptron, Multi Layer Perceptron, Self Organizing Maps, Hopfield Network.
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