Learning agents · game AI · research
Engineering the first self-taught Tales of Tribute agent
via deep RL and abstract action selection.
Tales of Tribute, or ToT, is an online card game that was particularly hard for AI to play. Imperfect information, a large and dynamic action space, and abstract long-term planning each contributed to make the game a particularly tough reasoning challenge for AI to crack.
As a result, agents at the time required human domain knowledge in order to function. While in high school, I engineered the first RL agent for the game, which learned without human knowledge and approximately matched or beat most baseline domain-knowledge agents.
Publication · IEEE Conference on Games 2025
Training a Reinforcement Learning Agent for Tales of Tribute
Sebastian Lashmet & Alexander Dockhorn · 2025
Read the paper on IEEE Xplore ↗Selected research awards
JSHS Nationals 20252nd place in computer science and mathematics
Junior Science and Humanities Symposium (JSHS) 2025, New York region5th place overall
Dr. Robert Pavlica Science Research Award
Downstate Tri-County Science Fair1st place overall
Westchester Science and Engineering Fair 20253rd place in computer science and mathematics
UAlbany Inaugural High School Research Symposium2nd place overall
Somers Science Fair 20233rd place in computer science and mathematics