Charles Pilkington

I grew up on a farm in Lancashire, in the North of England, surrounded by more fields and livestock than computers and technology. Growing up outside a major city meant that I had considerably less exposure to technology and the internet than many people my age. Despite this, I developed a strong interest in Computer Science and found that I particularly enjoyed the process of breaking down difficult problems and finding simple, elegant solutions to them. That interest eventually led me to study Computer Science at the University of Oxford.

I am particularly interested in Machine Learning, and especially Reinforcement Learning, because of the way an agent can develop strategies through experience rather than being explicitly taught how to solve a problem. I find it fascinating to watch models discover tactics in games such as chess that a human may never have thought of. I am also particularly interested in multi-agent settings, where multiple agents interact and must make decisions while accounting for the behaviour of others. Zero-sum games are especially intriguing to me because the agents' objectives are directly opposed: a gain in reward for one agent corresponds to a loss for another. This naturally connects Reinforcement Learning with areas such as game theory and probabilistic decision-making, which are areas I am keen to explore further.

Outside of my studies, I play tennis and enjoy spending time with friends. I am also a particularly enthusiastic cat person, and have always loved having cats around. When I am not studying or playing tennis, I enjoy simply getting out and about rather than spending all my time in front of a computer.