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Biases for Emergent Communication in Multi-agent Reinforcement Learning
We study the problem of emergent communication, in which language arises...
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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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Emergent Coordination Through Competition
We study the emergence of cooperative behaviors in reinforcement learnin...
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Human-level performance in first-person multiplayer games with population-based deep reinforcement learning
Recent progress in artificial intelligence through reinforcement learnin...
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Value-Decomposition Networks For Cooperative Multi-Agent Learning
We study the problem of cooperative multi-agent reinforcement learning w...
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Nesterov's Accelerated Gradient and Momentum as approximations to Regularised Update Descent
We present a unifying framework for adapting the update direction in gra...
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A Gauss-Newton Method for Markov Decision Processes
Approximate Newton methods are a standard optimization tool which aim to...
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Conditional mean embeddings as regressors - supplementary
We demonstrate an equivalence between reproducing kernel Hilbert space (...
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