Artificial Intelligence detailed syllabus scheme for Computer Engineering (CE), 2019-20 onwards has been taken from the DBATU official website and presented for the Bachelor of Technology students. For Subject Code, Course Title, Lecutres, Tutorials, Practice, Credits, and other information, do visit full semester subjects post given below.
For 6th Sem Scheme of Computer Engineering (CE), 2019-20 Onwards, do visit CE 6th Sem Scheme, 2019-20 Onwards. For the Elective-V scheme of 6th Sem 2019-20 onwards, refer to CE 6th Sem Elective-V Scheme 2019-20 Onwards. The detail syllabus for artificial intelligence is as follows.
Artificial Intelligence Syllabus for Computer Engineering (CE) 3rd Year 6th Sem 2019-20 DBATU
UNIT 1
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UNIT 2
Problem-solving Solving Problems by Searching, Problem-Solving Agents, Example Problems, Searching for Solutions, Uninformed Search Strategies, Informed (Heuristic) Search Strategies, Heuristic Functions.
UNIT 3
Constraint Satisfaction Problems Defining Constraint Satisfaction Problems, Constraint Propagation: Inference in CSPs, Backtracking Search for CSPs, Local Search for CSPs, The Structure of Problems.
UNIT 4
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UNIT 5
Logical Agents Knowledge-Based Agents, The Wumpus World, Logic, Propositional Logic: A Very Simple Logic, Propositional Theorem Proving, Effective Propositional Model Checking, Agents Based on Propositional Logic First-Order Logic Representation Revisited Syntax and Semantics of First-Order Logic, Using First-Order Logic, Knowledge Engineering in First-Order Logic, Inference in First-Order Logic, Propositional vs. First-Order Inference, Unification and Lifting, Forward Chaining, Backward Chaining, Resolution.
UNIT 6
Uncertainty Quantifying Uncertainty, Acting under Uncertainty, Basic Probability Notation, Inference Using Full Joint Distributions, Independence, Bayes Rule and Its Use, The Wumpus World Revisited, Probabilistic Reasoning, Representing Knowledge in an Uncertain Domain, The Semantics of Bayesian Networks, Efficient Representation of Conditional Distributions Exact Inference in Bayesian Networks, Approximate Inference in Bayesian Networks, Relational and First-Order Probability Models, and Other Approaches to Uncertain Reasoning.
Reference Books:
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For detail syllabus of all subjects of Computer Engineering (CE) 6th Sem 2019-20 onwards, visit CE 6th Sem Subjects of 2019-20 Onwards.