OVERVIEW

The course introduces to the main themes of deductive-based Artificial Intelligence with a focus on practical applications on Knowledge Representation and Planning.

AIMS AND CONTENT

LEARNING OUTCOMES

The course consists of two modules, which together provide a comprehensive introduction to the principles and applications of AI techniques in autonomous robotic systems. Overall, the course aims to equip students with the theoretical understanding and practical tools needed to design and implement intelligent, autonomous robotic systems capable of operating in complex environments.

PREREQUISITES

Some preliminary knowledge of combinatorics, algebra and theoretical computer science are useful for a better understanding of the course material.

TEACHERS AND EXAM BOARD

EXAMS

EXAM DESCRIPTION

The class consists of two modules, and the final exam mark is obtained from the marks of intermediate tests and projects from both modules. Please refer to each module for a detailed description of its respective intermediate tests and projects.

ASSESSMENT METHODS

The class is divided into two modules, with specific assessment methods for each module’s learning outcomes detailed within the corresponding module descriptions.