Cooperative and Non-Cooperative artificial intelligence (AI)

For my project I intend to study how AI agents can learn to cooperate with one another and take advantage of one another in general sum games. The games will be social dilemmas, meaning the players of these games can make a personal choice to increase their reward, at the detriment to the welfare of the other players. To begin my study of this topic I first intend to do an information theoretical study of various deterministic strategies used to play the prisoners dilemma (a simple social dilemma), as outlined by Axelrod, as well as including simple naïve learning agents. This should allow me to outline metrics that can be used to classify strategies, by asking questions such as, does this strategy rely on a transfer of information from its opponent? If it does, does it use this information to reciprocate behaviours? Once these strategies have been classified using information theoretic metrics it should be possible to detect agents that change strategy, including agents who try go from cooperating with their opponent to then trying to exploit them. Allowing us to prepare agents who can detect and react to deceptive behaviours from their opponent. Finally, we expect it to be possible to use these metrics to try and inform the design of deep reinforcement learning agents that can learn to take advantage of their opponent.

The EPSRC Centre for Doctoral Training in Cybersecurity will train over 55 experts in multi-disciplinary aspects of cybersecurity, from engineering to crime science and public policy.

Short term impacts are associated with the research outputs of the 55+ research projects that will be undertaken as part of the doctoral studies of CDT students. Each project will tackle an important cybersecurity problem, propose and evaluate solutions, interventions and policy options. Students will publish those in international peer-reviewed journals, but also disseminate those through blog posts and material geared towards decision makers and experts in adjacent fields. Through industry placements relating to their projects, all students will have the opportunity to implement and evaluate their ideas within real-world organizations, to achieve short term impact in solving cybersecurity problems.

In the longer term graduates of the CDT will assume leading positions within industry, goverment, law enforcement, the third sector and academia to increase the capacity of the UK in being a leader in cybersecurity. From those leadership positions they will assess options and formulate effective interventions to tackle cybercrime, secure the UK's infrastructure, establish norms of cooperation between industries and government to secure IT systems, and become leading researcher and scholars further increasing the UK's capacity in cybersecurity in the years to come. The last impact is likely to be significant give that currently many higher education training programs do not have capacity to provide cybersecurity training at undergraduate or graduate levels, particularly in non-technical fields.

The full details of our plan to achieve impact can be found in the "Pathways to Impact" document.