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Artificial Intelligence

Pre-requisites, Course Objectives and outcomes

Pre-requisites: Data Structures & Algorithms, Computer Architecture, Discrete Mathematical Structures

Course Objectives

To understand concept of Artificial Intelligence, its roots, sub-domains, Turing test

To understand concepts advanced topics in propositional formulas, syntax and semantics, human reasoning patterns & their formal notations, rule-based systems, logic programming, real-world knowledge representation and reasoning, Network-based representation and reasoning, conceptual graphs, semantic networks, frames, conceptual graphs and description logic.

To understand the concepts of state space search, heuristic search, constraint satisfation problems, adversarial search, game theory and its applications

To understand the concepts of probabilistic reasoning, Machine learning, statistical learning theory, (robotic) planning and intelligent agents.

To understand the concepts of data mining, Information Retrieval NLP, parsing theories, and question answering.

To understand the concepts of automatic speech recognition and Machine Vision.

Module 1: Introduction, AI Goals, Knowledge representation & Reasoning

Module 2: Forward and backward chaining & Prolog

Module 3: Special topics on knowledge representation & heuristic search

Module 4: Constrait satisfaction problems, Game playing, alpha-beta serch, Planning, & multi-agent systems

Module 5: Homework/Quizzes/Exam:

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