Distributed Reinforcement Learning via Gossip

2013-10-28 · Adwaitvedant S. Mathkar, Vivek S. Borkar

We consider the classical TD(0) algorithm implemented on a network of agents wherein the agents also incorporate the updates received from neighboring agents using a gossip-like mechanism. The combined scheme is shown to converge for both discounted and average cost problems.

📄 PDF Abstract BibTeX arXiv:1310.7610

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reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning

2019-06-09 · NeurIPS 2019 12 · Mahmoud Assran, Joshua Romoff, Nicolas Ballas, Joelle Pineau 외

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Bilevel optimization have gained growing interests, with numerous applications found in meta learning, minimax games, reinforcement learning, and nested composition optimization. This paper studies the problem of distrib…

Bilevel Optimization Federated Learning Meta-Learning reinforcement-learning+2

Common Knowledge in a Logic of Gossips

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Gossip protocols aim at arriving, by means of point-to-point or group communications, at a situation in which all the agents know each other secrets. Recently a number of authors studied distributed epistemic gossip prot…

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Distributed deep learning is an effective way to reduce the training time of deep learning for large datasets as well as complex models. However, the limited scalability caused by network overheads makes it difficult to …