Theory and implementation of a variety of techniques used to simulate intelligent behavior. Expert systems, fuzzy logic, neural networks, evolutionary computation, and two-player game-tree search will be covered in depth. Knowledge representation, pattern recognition, hybrid approaches, and handling uncertainty will also be discussed Objective
By covering the course in Intelligent Systems, the student will be able to:Appreciate the concepts of Artificial Intelligence and the diversity of approaches and definitions with which it is associated.
Develop an understanding of heuristic methods.
Learn the underlying theory and practice of evolutionary computation, including genetic algorithms and genetic programming.
- Appreciate knowledge engineering, develop expert systems, and understand fuzzy expert systems.
- Develop an understanding of and implement artificial neural networks.
- Implement a two-player strategy game with optimized adversarial search.
- Implement, observe and evaluate alternative approaches to intelligent systems
|Attachment Name||Attachment Type|
|CMP3205 Intelligent System||DOC||PS|