Shayegan Omidshafiei

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MIT

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 ...
11/18/2020 ∙ by Karl Tuyls, et al. ∙ 11 ∙ share

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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 ...
05/04/2020 ∙ by Shayegan Omidshafiei, et al. ∙ 11 ∙ share

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Real World Games Look Like Spinning Tops

This paper investigates the geometrical properties of real world games (...
04/20/2020 ∙ by Wojciech Marian Czarnecki, et al. ∙ 10 ∙ share

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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 ...
02/19/2020 ∙ by Julien Perolat, et al. ∙ 32 ∙ share

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A Generalized Training Approach for Multiagent Learning

This paper investigates a population-based training regime based on game...
09/27/2019 ∙ by Paul Müller, et al. ∙ 20 ∙ share

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Multiagent Evaluation under Incomplete Information

This paper investigates the evaluation of learned multiagent strategies ...
09/21/2019 ∙ by Mark Rowland, et al. ∙ 24 ∙ share

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OpenSpiel: A Framework for Reinforcement Learning in Games

OpenSpiel is a collection of environments and algorithms for research in...
08/26/2019 ∙ by Marc Lanctot, et al. ∙ 12 ∙ share

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Neural Replicator Dynamics

In multiagent learning, agents interact in inherently nonstationary envi...
06/01/2019 ∙ by Shayegan Omidshafiei, et al. ∙ 12 ∙ share

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Policy Distillation and Value Matching in Multiagent Reinforcement Learning

Multiagent reinforcement learning algorithms (MARL) have been demonstrat...
03/15/2019 ∙ by Samir Wadhwania, et al. ∙ 0 ∙ share

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Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning

Heterogeneous knowledge naturally arises among different agents in coope...
03/07/2019 ∙ by Dong-Ki Kim, et al. ∙ 6 ∙ share

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α-Rank: Multi-Agent Evaluation by Evolution

We introduce α-Rank, a principled evolutionary dynamics methodology, for...
03/04/2019 ∙ by Shayegan Omidshafiei, et al. ∙ 0 ∙ share

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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...
05/20/2018 ∙ by Shayegan Omidshafiei, et al. ∙ 0 ∙ share

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Crossmodal Attentive Skill Learner

This paper presents the Crossmodal Attentive Skill Learner (CASL), integ...
11/28/2017 ∙ by Shayegan Omidshafiei, et al. ∙ 0 ∙ share

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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 ...
07/24/2017 ∙ by Miao Liu, et al. ∙ 0 ∙ share

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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...
03/17/2017 ∙ by Shayegan Omidshafiei, et al. ∙ 0 ∙ share

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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...
03/16/2017 ∙ by Shayegan Omidshafiei, et al. ∙ 0 ∙ share

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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...
03/16/2017 ∙ by Shayegan Omidshafiei, et al. ∙ 0 ∙ share

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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...
02/20/2015 ∙ by Shayegan Omidshafiei, et al. ∙ 0 ∙ share

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Shayegan Omidshafiei

Featured Co-authors

Zhe Wang

Nicolas Heess

Remi Munos

Jonathan P. How

Michal Valko

Georgios Piliouras

Thore Graepel

Karl Tuyls

David Balduzzi

Marc Lanctot

Siqi Liu

Game Plan: What AI can do for Football, and What Football can do for AI

Navigating the Landscape of Multiplayer Games to Probe the Drosophila of AI

Real World Games Look Like Spinning Tops

From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization

A Generalized Training Approach for Multiagent Learning

Multiagent Evaluation under Incomplete Information

OpenSpiel: A Framework for Reinforcement Learning in Games

Neural Replicator Dynamics

Policy Distillation and Value Matching in Multiagent Reinforcement Learning

Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning

α-Rank: Multi-Agent Evaluation by Evolution

Learning to Teach in Cooperative Multiagent Reinforcement Learning

Crossmodal Attentive Skill Learner

Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions

Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability

Scalable Accelerated Decentralized Multi-Robot Policy Search in Continuous Observation Spaces

Semantic-level Decentralized Multi-Robot Decision-Making using Probabilistic Macro-Observations

Decentralized Control of Partially Observable Markov Decision Processes using Belief Space Macro-actions