Artificial Intelligence for JNTU-H 18 Course (IV - I - CSE / IT - CS713PE) - Professional Elective - IV & (IV - I - CSE / IT - CS701OE ) - Open Elective - II (Decode)

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UNIT - I Problem Solving by Search-I : Introduction to AI, Intelligent Agents Problem Solving by Search-II : Problem-Solving Agents, Searching for Solutions, Uninformed Search Strategies : Breadth-first search, Uniform cost search, Depth-first search, Iterative deepening Depth-first search, Bidirectional search, Informed (Heuristic) Search Strategies : Greedy best-first search, A* search, Heuristic Functions, Beyond Classical Search : Hill-climbing search, Simulated annealing search, Local Search in Continuous Spaces, Searching with Non-Deterministic Actions, Searching with Partial Observations, Online Search Agents and Unknown Environment . (Chapters - 1, 2, 3) UNIT - II Problem Solving by Search-II and Propositional Logic Adversarial Search : Games, Optimal Decisions in Games, Alpha-Beta Pruning, Imperfect Real-Time Decisions. Constraint Satisfaction Problems : Defining Constraint Satisfaction Problems, Constraint Propagation, Backtracking Search for CSPs, Local Search for CSPs, The Structure of Problems. Propositional Logic : Knowledge-Based Agents, The Wumpus World, Logic, Propositional Logic, Propositional Theorem Proving : Inference and proofs, Proof by resolution, Horn clauses and definite clauses, Forward and backward chaining, Effective Propositional Model Checking, Agents Based on Propositional Logic.(Chapters - 4, 5, 6, 7) UNIT - III Logic and Knowledge Representation First - Order Logic : Representation, 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. Knowledge Representation : Ontological Engineering, Categories and Objects, Events. Mental Events and Mental Objects, Reasoning Systems for Categories, Reasoning with Default Information. (Chapters - 8, 9) UNIT - IV Planning Classical Planning : Definition of Classical Planning, Algorithms for Planning with State-Space Search, Planning Graphs, other Classical Planning Approaches, Analysis of Planning approaches. Planning and Acting in the Real World : Time, Schedules, and Resources, Hierarchical Planning, Planning and Acting in Nondeterministic Domains, Multi agent Planning. (Chapters - 10, 11) UNIT - V Uncertain knowledge and Learning Uncertainty : Acting under Uncertainty, Basic Probability Notation, Inference Using Full Joint Distributions, Independence, Bayes’ Rule and Its Use, Probabilistic Reasoning : Representing Knowledge in an Uncertain Domain, The Semantics of Bayesian Networks, Efficient Representation of Conditional Distributions, Approximate Inference in Bayesian Networks, Relational and First-Order Probability, Other Approaches to Uncertain Reasoning; Dempster - Shafer theory. Learning : Forms of Learning, Supervised Learning, Learning Decision Trees. Knowledge in Learning : Logical Formulation of Learning, Knowledge in Learning, Explanation - Based Learning, Learning Using Relevance Information, Inductive Logic Programming. (Chapters - 12, 13)

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Author: [Anamitra Deshmukh-Nimbalkar] Pages: 244 Edition: 2021 Vendors: Technical Publications