Elastic Monte Carlo Tree Search with State Abstraction for Strategy Game Playing

1 code implementation • 30 May 2022 • Linjie Xu, Jorge Hurtado-Grueso, Dominic Jeurissen, Diego Perez Liebana, Alexander Dockhorn

In this paper, we propose Elastic MCTS, an algorithm that uses state abstraction to play strategy games.

The MineRL 2019 Competition on Sample Efficient Reinforcement Learning using Human Priors

1 code implementation • 22 Apr 2019 • William H. Guss, Cayden Codel, Katja Hofmann, Brandon Houghton, Noboru Kuno, Stephanie Milani, Sharada Mohanty, Diego Perez Liebana, Ruslan Salakhutdinov, Nicholay Topin, Manuela Veloso, Phillip Wang

To that end, we introduce: (1) the Minecraft ObtainDiamond task, a sequential decision making environment requiring long-term planning, hierarchical control, and efficient exploration methods; and (2) the MineRL-v0 dataset, a large-scale collection of over 60 million state-action pairs of human demonstrations that can be resimulated into embodied trajectories with arbitrary modifications to game state and visuals.

Decision Making Efficient Exploration +2