Artificial Intelligence detailed syllabus for Artificial Intelligence & Machine Learning (AI&ML) for 2021 regulation curriculum has been taken from the Anna University official website and presented for the AI&ML students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Artificial Intelligence & Machine Learning 4th Sem scheme and its subjects, do visit AI&ML 4th Sem 2021 regulation scheme. The detailed syllabus of artificial intelligence is as follows.
Course Objectives:
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Unit I
INTELLIGENT AGENTS 9 Introduction to AI – Agents and Environments – concept of rationality – nature of environments -structure of agents. Problem solving agents – search algorithms – uninformed search strategies.
Unit II
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Unit III
GAME PLAYING AND CSP 9 Game theory – optimal decisions in games – alpha-beta search – monte-carlo tree search -stochastic games – partially observable games. Constraint satisfaction problems – constraint propagation – backtracking search for CSP – local search for CSP – structure of CSP.
Unit IV
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Unit V
PROBABILISTIC REASONING 9 Acting under uncertainty – Bayesian inference – naive Bayes models. Probabilistic reasoning -Bayesian networks – exact inference in BN – approximate inference in BN – causal networks.
Course Outcomes:
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Reference Books:
- Dan W. Patterson, Introduction to AI and ES, Pearson Education,2007
- Kevin Night, Elaine Rich, and Nair B., Artificial Intelligence, McGraw Hill, 2008
- Patrick H. Winston, “Artificial Intelligence”, Third Edition, Pearson Education, 2006
- Deepak Khemani, Artificial Intelligence, Tata McGraw Hill Education, 2013.
- http://nptel.ac.in/
For detailed syllabus of all other subjects of Artificial Intelligence & Machine Learning, 2021 regulation curriculum do visit AI&ML 4th Sem subject syllabuses for 2021 regulation.
For all Artificial Intelligence & Machine Learning results, visit Anna University AI&ML all semester results direct link.