Artificial Intelligence detailed Syllabus for Master of Computer Applications (MCA), R19 regulation has been taken from the JNTUH official website and presented for the students affiliated to JNTUH course structure. For Course Code, Subject Names, Theory Lectures, Tutorial, Practical/Drawing, Credits, and other information do visit full semester subjects post given below. The Syllabus PDF files can also be downloaded from the universities official website.
For all the other MCA 2nd Year 2nd Sem Syllabus for R19 Regulation JNTUH, visit Master of Computer Applications 2nd Year 2nd Sem R19 Scheme.
For all the (Professional Elective-I) subjects refer to Professional Elective-I Scheme. The detail syllabus for artificial intelligence is as follows.
Course Objectives:
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Course Outcomes:
- Ability to formulate an efficient problem space for a problem expressed in natural language.
- Select a search algorithm for a problem and estimaate its time and space complexities.
- Possess the skill for representing knowledge using the appropriate technique for a given problem.
- Possess the ability to apply AI techniques to solve problems of game playing, and machine learning.
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 wih Partial Observations, Online Search Agents and Unknown Environment .
Unit II
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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.
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,.
Unit V
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Text Books:
- Artificial Intelligence A Modern Approach, Stuart Russell and Peter Norvig, 3rd Edition, Pearson Education.
Reference Books:
- Artificial Intelligence , 3rd Edn. , E.Rich and K.Knight (TMH)
- Artificial Intelligence, 3rd Edn., Patrick Henny Winston, Pearson Education.
- Artificial Intelligence, Shivani Goel, Pearson Education.
- Artificial Intelligence and Expert systems – Patterson, Pearson Education.
For detail Syllabus of all other subjects of 2nd Year 2nd Sem Master of Computer Applications, visit MCA 2nd Year 2nd Sem Syllabus Subjects.
For all MCA results, visit JNTUH MCA all years, and semester results from direct links.