142 citations · 150 across the 2 of their papers we have counts for
5 papers · 1 filter
The Advantage Regret-Matching Actor-Critic
Audrūnas Gruslys, Marc Lanctot, Rémi Munos +10
Regret minimization has played a key role in online learning, equilibrium computation in games, and reinforcement learning (RL). In this paper, we describe a general model-free RL…
Navigating the Landscape of Multiplayer Games
Shayegan Omidshafiei, Karl Tuyls, Wojciech M. Czarnecki +9
Multiplayer games have long been used as testbeds in artificial intelligence research, aptly referred to as the Drosophila of artificial intelligence. Traditionally, researchers ha…
Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents
Joel Z. Leibo, Cyprien de Masson d'Autume, Daniel Zoran +10
Psychlab is a simulated psychology laboratory inside the first-person 3D game world of DeepMind Lab (Beattie et al. 2016). Psychlab enables implementations of classical laboratory…
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning
Marc Lanctot, Vinicius Zambaldi, Audrunas Gruslys +5
To achieve general intelligence, agents must learn how to interact with others in a shared environment: this is the challenge of multiagent reinforcement learning (MARL). The simpl…
Value-Decomposition Networks For Cooperative Multi-Agent Learning
Peter Sunehag, Guy Lever, Audrunas Gruslys +8
We study the problem of cooperative multi-agent reinforcement learning with a single joint reward signal. This class of learning problems is difficult because of the often large co…