Unit 1 Biological foundations to intelligent systems I

9 lecture hours

• Artificial neural networks
• Back propagation networks
• Radial basis function networks, and recurrent networks

Unit 2 Biological foundations to intelligent systems II

8 lecture hours

• Fuzzy logic
• knowledge Representation and inference mechanism
• genetic algorithm, and fuzzy neural networks

Unit 3 Search Methods Basic concepts of graph and tree search. Three

8 lecture hours

• simple search methods: breadth-first search
• depth-first search
• iterative deepening search
• Heuristic search methods: best-first search
• admissible evaluation functions
• hill climbing search
• Optimisation and search such as stochastic annealing and genetic algorithm

Unit 4 Knowledge representation and logical inference Issues in knowledge

9 lecture hours

• Structured representation
• such as frames, and scripts
• semantic networks and conceptual graphs
• Formal logic and logical inference
• Knowledge-based systems structures
• its basic components
• Ideas of Blackboard architectures

Unit 5 Reasoning under uncertainty and Learning Techniques on

8 lecture hours

• uncertainty reasoning such as Bayesian reasoning
• Certainty factors and Dempster-Shafer Theory of Evidential reasoning
• A study of different learning and evolutionary algorithms
• such as statistical learning and induction learning

Unit 6 Recent trends in Fuzzy logic, Knowledge Representation 5 6 10% References

• Luger G.F. and Stubblefield W.A
• Artificial Intelligence: Structures and strategies for Complex Problem Solving
• Addison Wesley
• 6th edition. 2
• Russell S. and Norvig P
• Artificial Intelligence: A Modern Approach
• 3rd edition. 3
• Alexander M Meystel and James S Albus
• Intelligent Systems