Artificial Intelligence

THSP743: Artificial Intelligence. This module explores the fundamental principles of artificial intelligence (AI), providing students with a comprehensive introduction to the core concepts that define the field. The curriculum is designed to familiarize students with both conventional approaches to AI and more advanced topics such as machine learning and knowledge representation.

Machine Learning and Knowledge. Students are introduced to the concept of machine learning, gaining an understanding of how systems can be designed to learn from data and improve their performance over time. The module also covers the representation and processing of knowledge, which is essential for intelligent decision-making in AI systems.

Conventional AI and Computational Intelligence. In addition to foundational AI methods, the module provides an overview of evolutionary computation and the broader field of computational intelligence. These topics examine algorithms inspired by natural processes and their application to complex problem-solving scenarios.

Applications in Robotics: Neuro-Fuzzy Systems. The module presents practical applications of AI in robotics, focusing on the use of neuro-fuzzy systems. Emphasis is placed on understanding the fundamentals of fuzzy logic, which enables robots to handle uncertainty and approximate reasoning, and on techniques for effective problem solving in robotic contexts.

Reasoning Systems. Students examine different types of reasoning systems, including both deductive reasoning, which derives specific conclusions from general rules, and inductive reasoning, which infers general principles from specific examples. The module ensures students can distinguish and apply these approaches within AI frameworks.

Neural Networks. The curriculum covers both feedforward and recurrent neural networks. These models are explored with attention to their architecture and functionalities, providing students with foundational knowledge of how neural networks process information.

Introduction to Natural Language Processing. Finally, the module introduces the basics of Natural Language Processing (NLP), outlining how AI systems can be developed to understand and process human language. This section sets the stage for further study and application of NLP technologies.