A
Aviv Tamar
Researcher at Technion – Israel Institute of Technology
Publications - 111
Citations - 7986
Aviv Tamar is an academic researcher from Technion – Israel Institute of Technology. The author has contributed to research in topics: Reinforcement learning & Computer science. The author has an hindex of 31, co-authored 97 publications receiving 5310 citations. Previous affiliations of Aviv Tamar include Cornell University & Facebook.
Papers
More filters
Posted Content
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
TL;DR: An adaptation of actor-critic methods that considers action policies of other agents and is able to successfully learn policies that require complex multi-agent coordination is presented.
Proceedings Article
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
TL;DR: In this article, an actor-critic method was used to learn multi-agent coordination policies in cooperative and competitive multi-player RL games, where agent populations are able to discover various physical and informational coordination strategies.
Proceedings Article
Constrained policy optimization
TL;DR: Constrained Policy Optimization (CPO) as discussed by the authors is the first general-purpose policy search algorithm for constrained reinforcement learning with guarantees for near-constraint satisfaction at each iteration.
Posted Content
Value Iteration Networks
TL;DR: The Value Iteration Network (VIN) as discussed by the authors is a differentiable approximation of the value iteration algorithm, which can be represented as a convolutional neural network and trained end-to-end using standard backpropagation.
Posted Content
Model-Ensemble Trust-Region Policy Optimization
TL;DR: The authors proposed to use an ensemble of models to maintain the model uncertainty and regularize the learning process, which significantly reduces the sample complexity compared to model-free deep RL methods on challenging continuous control benchmark tasks.