ME-703 (B) · Artificial Intelligence Techniques/Official Syllabus
Artificial Intelligence Techniques (ME-703 (B)) - Official Syllabus
1
Unit 1
Introduction to Artificial Intelligence
- Main components and characteristics of AI (Feature Engineering, ANN, Deep Learning)
- Applications of AI
- Advantages and disadvantages of AI
- Goals of AI
- Comparision of Programming of a System with AI and without AI
- Challenges in AI
- Programming languges preferably used in AI
- Techniques/Algorithms used in AI
- AI Software plaforms
- Future of AI
2
Unit 2
Various types of production systems and search techniques
- Types of production systems
- Characteristics of production systems
- Study and comparison of breadth first search and depth first search
- Techniques, other Search Techniques like hill Climbing, Best first Search
- A* algorithm, AO* algorithms etc
- various types of control strategies
3
Unit 3
Knowledge Representation and Probabilistic Reasoning
- Problems in representing knowledge
- knowledge representation using propositional and predicate logic
- comparison of propositional and predicate logic
- Resolution, refutation, deduction, theorem proving, inferencing
- monotonic and nonmonotonic reasoning
- Probabilistic reasoning, Baye's theorem
- semantic networks, scripts, schemas, frames, conceptual dependency
- fuzzy logic
- forward and backward reasoning
4
Unit 4
Game playing techniques
- Minimax procedure, alpha-beta cut-offs etc
- planning
- Study of the block world problem in robotics
- Introduction to understanding and natural languages processing
5
Unit 5
Introduction to learning, ANN
- Various techniques used in learning
- introduction to Artificial neural networks, common sense, reasoning
- Convolution Neural Network
- Feedforward Neural Network
- Recurrent Neural Network
- Multilayer perceptron
- Architecture / Three Layers in Artificial Neural Networks
- Implementation of ANN
- Applications of ANN in images, signals and language some example of expert systems
Reference Books
- Rich E and Knight K, Artificial Intelligence, TMH, New Delhi.
- Nelsson N.J., Principles of Artificial Intelligence, Springer Verlag, Berlin.
- Stuart Russell, Artificial Intelligence: A Modern Approach, Peter Norvig, PHI
- B. Yegnanarayana, Artificial Neural Networks, PHI
- Schalkoff, Artificial Neural Networks. Mc Graw HILL Education
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