42 citations · 113 across the 7 of their papers we have counts for
8 papers
A team of Gemini 4 Argon agents beats Minecraft
Maxence Faldor, Satinder Singh, Roberta Raileanu
We placed four Gemini 4 Argon agents in a sandboxed Minecraft survival world and gave them one goal: defeat the Ender Dragon. Each agent controlled a player via an open-source libr…
Efficient Querying for Cooperative Probabilistic Commitments
Qi Zhang, Edmund H. Durfee, Satinder Singh
Multiagent systems can use commitments as the core of a general coordination infrastructure, supporting both cooperative and non-cooperative interactions. Agents whose objectives a…
Hindsight Credit Assignment
Anna Harutyunyan, Will Dabney, Thomas Mesnard +8
We consider the problem of efficient credit assignment in reinforcement learning. In order to efficiently and meaningfully utilize new data, we propose to explicitly assign credit…
Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem
John Holler, Risto Vuorio, Zhiwei Qin +6
Order dispatching and driver repositioning (also known as fleet management) in the face of spatially and temporally varying supply and demand are central to a ride-sharing platform…
No Press Diplomacy: Modeling Multi-Agent Gameplay
Philip Paquette, Yuchen Lu, Steven Bocco +6
Diplomacy is a seven-player non-stochastic, non-cooperative game, where agents acquire resources through a mix of teamwork and betrayal. Reliance on trust and coordination makes Di…
Learning Independently-Obtainable Reward Functions
Christopher Grimm, Satinder Singh
We present a novel method for learning a set of disentangled reward functions that sum to the original environment reward and are constrained to be independently obtainable. We def…