I am a PhD student based in the Centre for Complexity Science at the University of Warwick, supervised by Professor Matthew Turner.
My project has been looking at using the principle which we call future state maximisation as an intrinsic motivation for decision making. This is the idea that, taking everything else to be equal, generally it is preferable to make decisions that maximally keep your options open. The rationale for this is that in an uncertain world preparing yourself to deal with the widest range of potential future scenarios represents an attempt to maximise the amoiunt of control you have over your future environment. This is a principle with potentially wide ranging applicability as it can essentially be applied to any decision making agent in any environment, and intuitively should often lead to "intelligent" behaviour such as the development of reusable skills. Our approach is largely inspired by the empowerment and causal entropic forces frameworks, and our main application has been to a model of collective motion. Here a group of agents move so as to maximise the amount of control they have over the potential future visual states they can access. Simply by each agent following this simple rule a swarm spontaneously emerges which is highly aligned and cohesive with rich dynamics, as well as reproducing a number of features observed in real flocks of starlings. See research for more information.
More generally my research interests are in nonequilibrium statistical mechanics and in recent years I have become very interested in machine learning too, particularly reinforcement learning. In my spare time I have been working on a project where I have been using self-play deep reinforcement learning to train an AI to play a game called "Big 2". This is a four player game of imperfect information with a relatively complex action space, and so represents an interesting challenge. However, the AI is now at the stage where it comfortably beats amateur human players, and has yet to be tested against higher level players. Details of the project can be found on its GitHub page, and I also recently added a paper on the arXiv describing what I did. You can even play against the AI here, although it may take a while to load as I am using a free Heroku node to host it.
- MSc in Mathematics for Real-World Systems awarded with distinction (2015)
- Graduated from University College London in September 2014 with an MSci in Physics. First class honours and included on the Dean's List for Academic Excellence. My final year project was on "Entropy Production in Small Systems" and supervised by Professor Ian Ford.
- In the summer of 2012 I did a 10 week summer project funded by the EPSRC at the Research Complex at Harwell on "Optical Ptychography", supervised by Professor Ian Robinson and Dr Fucai Zhang.
You may have seen me at the following:
- Gaussian Processes Summer School (03-06 September, 2018)
- Fundamental Problems in Statistical Physics Summer School (FPSP XIV, 16-29 July 2017, Bruneck) Here is the poster I presented.
- Introduction to Machine Learning Summer School, 21-23 June 2017, University of Warwick
- Beijing Summer School on Nonequilibrium Statistical Physics and Active Matter (Chinese Academy of Sciences, 08-20 August 2016. Read about it in my IOP blog entry!)
- Principles of Biological and Robotic Navigation (BioNav16) (Max Planck Institute for the Physics of Complex Systems, Dresden, 29-31 August 2016). Here is the poster I presented.
- European Study Group With Industry (ESGI 116, University of Durham, 11-15 April 2016)