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Joshua Romoff

Alumni

Publications

Improving Intrinsic Exploration by Creating Stationary Objectives
Roger Creus Castanyer
Joshua Romoff
Glen Berseth
2024-01-16
ICLR.cc/2024/Conference (poster)
doi.org
openreview.net
Minimax Exploiter: A Data Efficient Approach for Competitive Self-Play
Daniel Bairamian
Philippe Marcotte
Joshua Romoff
Gabriel Robert
Derek Nowrouzezahrai
2024-01-01
AAMAS (publié)
doi.org
arxiv.org
Improving Intrinsic Exploration by Creating Stationary Objectives
Roger Creus Castanyer
Joshua Romoff
Glen Berseth
2023-10-27
ArXiv (prépublication)
doi.org
arxiv.org
Direct Behavior Specification via Constrained Reinforcement Learning
Julien Roy
Roger Girgis
Joshua Romoff
Pierre-Luc Bacon
Chris J Pal
Chris Pal
The standard formulation of Reinforcement Learning lacks a practical way of specifying what are admissible and forbidden behaviors. Most oft… (voir plus)en, practitioners go about the task of behavior specification by manually engineering the reward function, a counter-intuitive process that requires several iterations and is prone to reward hacking by the agent. In this work, we argue that constrained RL, which has almost exclusively been used for safe RL, also has the potential to significantly reduce the amount of work spent for reward specification in applied RL projects. To this end, we propose to specify behavioral preferences in the CMDP framework and to use Lagrangian methods to automatically weigh each of these behavioral constraints. Specifically, we investigate how CMDPs can be adapted to solve goal-based tasks while adhering to several constraints simultaneously. We evaluate this framework on a set of continuous control tasks relevant to the application of Reinforcement Learning for NPC design in video games.
2022-06-28
Proceedings of the 39th International Conference on Machine Learning (publié)
proceedings.mlr.press
arxiv.org