BE Computer Engineering Semester 7 (BE Fourth Year)University of Mumbai
Share
Notifications

View all notifications

Artificial Intelligence Semester 7 (BE Fourth Year) BE Computer Engineering University of Mumbai Topics and Syllabus

Login
Create free account


      Forgot password?
CBCGS [2019 - current]
CBGS [2015 - 2018]
Old [2000 - 2014]

Topics with syllabus and resources

100.00 Introduction to Artificial Intelligence
  • Introduction, History of Artificial Intelligence
  • Intelligent Systems:- Categorization of Intelligent System, Components of AI Program, Foundations of AI, Sub-areas of AI, Applications of AI, Current trends in AI.
200.00 Intelligent Agents
  • Agents and Environments
  • The concept of rationality
  • The nature of environment
  • The structure of Agents
  • Types of Agents
  • Learning Agent
300.00 Problem Solving
  • Solving problem by Searching:- Problem Solving Agent, Formulating Problems, Example Problems.
  • Uninformed Search Methods:- Breadth First Search (BFS), Depth First Search (DFS), Depth Limited Search, Depth First Iterative Deepening(DFID), Informed Search Methods:- Greedy best first Search ,A* Search, Memory bounded heuristic Search.
  • Local Search Algorithms and Optimization Problems:- Hillclimbing search Simulated annealing, Local beam search, Genetic algorithms.
  • Adversarial Search:- Games, Optimal strategies, The minimax algorithm, Alpha-Beta Pruning.
400.00 Knowledge and Reasoning
  • Knowledge based Agents, The Wumpus World, The Propositional logic, First Order Logic:- Syntax and Semantic, Inference in FOL, Forward chaining, backward Chaining.
  • Knowledge Engineering in First-Order Logic, Unification, Resolution, Introduction to logic programming (PROLOG).
  • Uncertain Knowledge and Reasoning:- Uncertainty, Representing knowledge in an uncertain domain, The semantics of belief network, Inference in belief network.
500.00 Planning and Learning
  • The planning problem, Planning with state space search, Partial order planning, Hierarchical planning, Conditional Planning.
  • Learning:- Forms of Learning, Inductive Learning, Learning Decision Tree.
  • Expert System:- Introduction, Phases in building Expert Systems, ES Architecture, ES vs Traditional System.
600.00 Applications
  • Natural Language Processing(NLP), Expert Systems.
S
View in app×