This module covers the principles of artificial intelligence and introduces the student to the concept of machine learning and knowledge. In addition to Conventional AI, the module also provides an overview of evolutionary computation and computational intelligence. Applications of robots using Neuro-fuzzy systems are presented with an emphasis on fundamentals of fuzzy logic and problem solving. The types of reasoning systems covered in this module include both deductive and inductive. Feedforward and recurrent networks are included in the module as well as an introduction to Natural Language Processing.
Learning Outcomes:
Upon completion of this module the student will be able to:
- Define the term artificial intelligence
- Name the two types of knowledge utilized by an AI system
- Explain the purpose of logical rules of inference
- Describe how expert systems are used in AI applications
- List the four parameters of case-based reasoning
- Define machine learning and how it applies to AI
- Differentiate between deductive and inductive reasoning
- Describe the purpose of evolutionary algorithms
- List the five main classifications of agents
- Compare feedforward networks with recurrent networks
- Explain the purpose of natural language processing (NLP)
- Name two types of AI robots
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