Search Results for author: Ashley J. Llorens

Found 3 papers, 2 papers with code

The AI Arena: A Framework for Distributed Multi-Agent Reinforcement Learning

1 code implementation9 Mar 2021 Edward W. Staley, Corban G. Rivera, Ashley J. Llorens

Advances in reinforcement learning (RL) have resulted in recent breakthroughs in the application of artificial intelligence (AI) across many different domains.

Multi-agent Reinforcement Learning OpenAI Gym +2

TanksWorld: A Multi-Agent Environment for AI Safety Research

1 code implementation25 Feb 2020 Corban G. Rivera, Olivia Lyons, Arielle Summitt, Ayman Fatima, Ji Pak, William Shao, Robert Chalmers, Aryeh Englander, Edward W. Staley, I-Jeng Wang, Ashley J. Llorens

In this work, we introduce the AI safety TanksWorld as an environment for AI safety research with three essential aspects: competing performance objectives, human-machine teaming, and multi-agent competition.

Decision Making

On the Complexity of Reconnaissance Blind Chess

no code implementations7 Nov 2018 Jared Markowitz, Ryan W. Gardner, Ashley J. Llorens

This paper provides a complexity analysis for the game of reconnaissance blind chess (RBC), a recently-introduced variant of chess where each player does not know the positions of the opponent's pieces a priori but may reveal a subset of them through chosen, private sensing actions.

Decision Making

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