CS40027: Artificial Intelligence

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CS40027
Course name Artificial Intelligence
Offered by Computer Science & Engineering
Credits 3
L-T-P 3-0-0
Previous Year Grade Distribution
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Semester Autumn


Syllabus[edit | edit source]

Syllabus mentioned in ERP[edit | edit source]

Problem solving by search: state space, problem reduction, game playing, constraint satisfaction; Automated Reasoning: proposition and first order logic, inference and deduction, resolution refutation, answer extraction, knowledge based systems, logic programming and constrained logic programming, non-monotonic reasoning; Planning: state-space, plan space and partial order planning, planning algorithms; Reasoning under uncertainty: probabilistic reasoning, belief networks; Learning: inductive learning, decision trees, logical approaches, computational learning theory, neural networks, reinforcement learning; Intelligent agents; natural language understanding; Applications.References1.Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Prentice-Hall.2.Nils J. Nilsson, Artificial Intelligence: A New Sythesis, Morgan-Kaufmann.


Concepts taught in class[edit | edit source]

Student Opinion[edit | edit source]

How to Crack the Paper[edit | edit source]

Classroom resources[edit | edit source]

Additional Resources[edit | edit source]