Thomas is a senior research scientist at Sony AI where he investigates the use of reinforcement learning in game-AI applications. He received his Ph.D. in computer science from Rutgers University and a B.S. in computer science from UMBC. Before joining Sony AI, Tom led an industry AI team focused on workforce applications and held research positions at MIT, the University of Kansas, and the University of Arizona. Tom’s previous research spans multiple domains including robotics, education, and logistics. His work has been published in top AI conferences and journals including AAAI, ICML, and NeurIPS.
“I am fascinated by the process of learning. At Sony AI, I study how AI agents explore their environments and how they react to different experiences and tasks. To do so, I construct training regimes to teach agents and develop illustrative tests to confirm the desired behaviors. This research helps us build exciting AI agents for games, but also teaches us about how AI and humans learn and adapt with new experiences.”
Outracing Champion Gran Turismo Drivers with Deep Reinforcement Learning
Many potential applications of artificial intelligence involve making real-time decisions in physical systems while interacting with humans. Automobile racing represents an extreme example of these conditions; drivers must execute complex tactical manoeuvres to pass or block…
April 4, 2022 | Sony AI
Meet the Team #4: Kenta, Alisa and Thomas
The next installments of our Meet the Team series will feature members of the global Sony AI team who contributed to thegroundbreaking research, Outracing Champion Gran Turismo Drivers with Deep Reinforcement Learning, and created…
The next installments of our Meet the Team series will feature members of the global Sony AI team who contributed to thegroundbrea…