Module finder

This module introduces students to the core principles, doctrines, and policy considerations underpinning Patent Law, Trade Marks, and Passing Off. It examines how legal frameworks protect innovation and commercial reputation while critically analysing the tensions between private monopoly rights and broader public interests, including competition, market access, consumer protection, and fairness within the intellectual property system. While this module builds on and reinforces core intellectual property foundations, it is designed as a standalone module and differs from the Level 6 module by focusing specifically on patents, trade marks, and passing off, and by developing a more sophisticated understanding of doctrinal complexity alongside critical assessment of the regulatory and societal consequences of intellectual property protection in innovation and branding.

Through a combination of doctrinal analysis and policy critique, the module provides a comprehensive understanding of how these rights operate in both UK and international frameworks, and how they interact with related areas such as competition law, social justice, and enforcement.

The first part of the module focuses on patent law, considering the justification for granting exclusive rights to inventors, the requirements for patentability, and the scope of protection afforded. It also analyses infringement and available defences, highlighting the tension between innovation incentives and technological progress.

The second part turns to the law of passing off and trade marks, addressing how law protects commercial goodwill, branding, and consumer trust. Students will examine the processes of registration, grounds for refusal, infringement, and defences, and will critically assess the impact of trade mark expansion on market competition and freedom of expression.

The module concludes with a study of IP and social justice, IP and competition law, and remedies and enforcement, encouraging students to evaluate the broader socio-economic implications of IP protection.

Key questions explored include: When does one company’s marketing cross the line into misrepresentation and passing off? Do trade marks promote consumer protection or stifle competition? How should trade mark law balance freedom of expression against brand reputation? What defences are available to alleged infringers of patents and trade marks? How can IP frameworks promote social justice and innovation simultaneously?

Students are encouraged to think critically about the philosophical, economic, and policy underpinnings of these regimes and to engage in independent research to explore contemporary issues in patent and trade mark law.

This module gives a broad introduction to the new and rapidly expanding field of agent-based computing. It introduces the key concepts and models of the field, dealing both with the individual agents and with their interactions. Particular emphasis is placed on automated negotiation, cooperation and on-line auctions, and students are required to program a trading agent in Java which will compete in a class tournament within a simulated trading environment.

This module gives a broad introduction to the new and rapidly expanding field of agent-based computing. It introduces the key concepts and models of the field, dealing both with the individual agents and with their interactions. Particular emphasis is placed on automated negotiation, cooperation and on-line auctions, and students are required to program a trading agent in Java which will compete in a class tournament within a simulated trading environment.

This module gives a broad introduction to the new and rapidly expanding field of agent-based computing. It introduces the key concepts and models of the field, dealing both with the individual agents and with their interactions. Particular emphasis is placed on automated negotiation, cooperation and on-line auctions, and students are required to program a trading agent in Java which will compete in a class tournament within a simulated trading environment.

This module gives a broad introduction to the new and rapidly expanding field of agent-based computing. It introduces the key concepts and models of the field, dealing both with the individual agents and with their interactions. Particular emphasis is placed on automated negotiation, cooperation and on-line auctions, and students are required to program a trading agent in Java which will compete in a class tournament within a simulated trading environment.

This module gives a broad introduction to the new and rapidly expanding field of agent-based computing. It introduces the key concepts and models of the field, dealing both with the individual agents and with their interactions. Particular emphasis is placed on automated negotiation, cooperation and on-line auctions, and students are required to program a trading agent in Java which will compete in a class tournament within a simulated trading environment.

This module teaches the theory and practice of robotic perception and reasoning needed for mobile autonomous vehicles to operate in dynamic, unstructured environments across land, sea and air. You will learn probabilistic methods so that robots can self-localise within and make sense of their surroundings. These methods will be implemented on real platforms to close the see-think-act loop for robust delivery of missions in complex fields that have not been designed to accommodate robots.

This module teaches the theory and practice of robotic perception and reasoning needed for mobile autonomous vehicles to operate in dynamic, unstructured environments across land, sea and air. You will learn probabilistic methods so that robots can self-localise within and make sense of their surroundings. These methods will be implemented on real platforms to close the see-think-act loop for robust delivery of missions in complex fields that have not been designed to accommodate robots.

This module teaches the theory and practice of robotic perception and reasoning needed for mobile autonomous vehicles to operate in dynamic, unstructured environments across land, sea and air. You will learn probabilistic methods so that robots can self-localise within and make sense of their surroundings. These methods will be implemented on real platforms to close the see-think-act loop for robust delivery of missions in complex fields that have not been designed to accommodate robots.

This module teaches the theory and practice of robotic perception and reasoning needed for mobile autonomous vehicles to operate in dynamic, unstructured environments across land, sea and air. You will learn probabilistic methods so that robots can self-localise within and make sense of their surroundings. These methods will be implemented on real platforms to close the see-think-act loop for robust delivery of missions in complex fields that have not been designed to accommodate robots.