Course

Problem solving: Graph based search, Algorithms for searching, Heuristic search, Robot path planning. Knowledge representation: Descriptive representation, Procedural representation, Rule-based representation, Semantic networks, Frames, Ontologies, Knowledge based systems. Expert systems. Artificial neural networks: Perceptron, Learning, Associative memories, Self-organised networks, Applications of neural networks in robotics. Deep learning applications for robotics. Fuzzy logic systems: Fuzzy logic, Fuzzy reasoning, Fuzzy logic-based techniques, Fuzzy relations, Fuzzy control, implementing fuzzy controllers, Fuzzy decision making. Genetic algorithms: Principles, Working, Design, Applications in robotics.

Suggested Lab Sessions:

·         Implement graph-based and heuristic search algorithms for robot navigation in MATLAB, Python

·        Design an expert system for diagnosing faults in a robotic arm using: Rule-based representation (if-then rules), Semantic networks for representing component relationships. Python (PyCLIPS for rule-based systems)

·         Apply neural network models for robotic perception tasks. MATLAB Neural Network Toolbox, Python (TensorFlow/Keras).

·        Implement fuzzy logic and genetic algorithm-based controllers for robot motion or task optimization. MATLAB Fuzzy Logic Toolbox, Python (scikit-fuzzy, DEAP for GA).

Course Outcomes:

CO1: Understand Problem solving: Graph based search, Algorithms for searching.

CO2: Understand Knowledge representation: Descriptive representation, Procedural  representation.

CO3: Analyze Semantic networks, Frames, Ontologies, Knowledge based systems.

CO4: Apply Artificial neural networks: Perceptron, Learning, Associative memories.

CO5: Apply Fuzzy logic systems: Fuzzy logic, Fuzzy reasoning.

CO6: Analyze Genetic algorithms: Principles, Working.

Textbooks / References:

1.      Russell, S.J. and Norvig, P., “Artificial Intelligence – A Modern Approach”, Prentice Hall, 2003.

2.      Negnewitsky, M., “A Guide to Intelligent Systems”, Addison-Wesley, 2005.

3.      Inger, G.F., “Artificial Intelligence: Structures and Strategies for Complex Problem Solving”, Addison-Wesley, 2005.

4.      Nilsson, N.J., “Artificial Intelligence: A New Synthesis”, Morgan-Kaufmann, 1998..