ACRL Preconferences: ACRL preconferences in San Francisco

16-899C ACRL Tetris Reinforcement Learner

Our approach to this problem was to use reinforcement learning with a function approximator to approximate the state value function [RSS98]. In our case, a +1 reward was given for every completed line, so that the value function would encode the long-term number of lines that is going to be completed by the algorithm. In order to achieve this, we extract features from the game state, and use gr...

UC San Francisco UC San Francisco Previously Published Works Title

Relocating to San Francisco

Relocating to San Francisco

Relocating to San Francisco