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Game Plan: What AI can do for Football, and What Football can do for AI
The rapid progress in artificial intelligence (AI) and machine learning ...
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Navigating the Landscape of Multiplayer Games to Probe the Drosophila of AI
Multiplayer games have a long history in being used as key testbeds for ...
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Real World Games Look Like Spinning Tops
This paper investigates the geometrical properties of real world games (...
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From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization
In this paper we investigate the Follow the Regularized Leader dynamics ...
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A Generalized Training Approach for Multiagent Learning
This paper investigates a population-based training regime based on game...
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Multiagent Evaluation under Incomplete Information
This paper investigates the evaluation of learned multiagent strategies ...
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OpenSpiel: A Framework for Reinforcement Learning in Games
OpenSpiel is a collection of environments and algorithms for research in...
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Neural Replicator Dynamics
In multiagent learning, agents interact in inherently nonstationary envi...
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Policy Distillation and Value Matching in Multiagent Reinforcement Learning
Multiagent reinforcement learning algorithms (MARL) have been demonstrat...
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Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning
Heterogeneous knowledge naturally arises among different agents in coope...
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α-Rank: Multi-Agent Evaluation by Evolution
We introduce α-Rank, a principled evolutionary dynamics methodology, for...
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Learning to Teach in Cooperative Multiagent Reinforcement Learning
We present a framework and algorithm for peer-to-peer teaching in cooper...
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Crossmodal Attentive Skill Learner
This paper presents the Crossmodal Attentive Skill Learner (CASL), integ...
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Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions
This paper presents a data-driven approach for multi-robot coordination ...
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Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability
Many real-world tasks involve multiple agents with partial observability...
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Scalable Accelerated Decentralized Multi-Robot Policy Search in Continuous Observation Spaces
This paper presents the first ever approach for solving continuous-obser...
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Semantic-level Decentralized Multi-Robot Decision-Making using Probabilistic Macro-Observations
Robust environment perception is essential for decision-making on robots...
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Decentralized Control of Partially Observable Markov Decision Processes using Belief Space Macro-actions
The focus of this paper is on solving multi-robot planning problems in c...
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