
Yourui S. 2025 | BASIS Independent Silicon Valley
- Project Title: Reinforcement Learning for Fish: a Social, Multiplayer Card Game
- BASIS Independent Advisor: Dr. Movshovitz
- Internship Location: Remote with Professor William Andreopoulos of San Jose State University
- Onsite Mentor: Professor William Andreopoulos, Department of Computer Science @ San Jose State University
Reinforcement Learning (RL) is a subset of AI that has long been used to optimize strategy in logic-based games such as Go and Chess. While Fish is a card game with logical components and tactics, gameplay is also affected by the unpredictability of human behavior, through disadvantageous risk-taking for the purpose of deception. In this remote project with assistance from Professor Andreopoulos of SJSU, I will investigate how RL agents can learn and adapt to human behavior as well as uncover new strategies in Fish. Through training an agent on collected real-world gameplay data and in self-play stages, testing different model frameworks and parameters, as well as evaluating results in play against optimal human players, I expect the final model to gain gameplay advantages but not exceed the most skilled human players capable of reading emotional and behavioral cues outside the agent’s view. In particular, I will analyze how the agent responds to unexpected, counterlogical human behavior, with implications in the larger field of socioaffective computing and human-assisting robotic agents.