Tabish Rashid | DeepAI

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∙ 01/25/2023

Imitating Human Behaviour with Diffusion Models

Diffusion models have emerged as powerful generative models in the text-...

0 Tim Pearce, et al. ∙

∙ 03/22/2021

Regularized Softmax Deep Multi-Agent Q-Learning

Tackling overestimation in Q-learning is an important problem that has b...

0 Ling Pan, et al. ∙

∙ 01/22/2021

Estimating α-Rank by Maximizing Information Gain

Game theory has been increasingly applied in settings where the game is ...

7 Tabish Rashid, et al. ∙

∙ 06/18/2020

Weighted QMIX: Expanding Monotonic Value Function Factorisation

QMIX is a popular Q-learning algorithm for cooperative MARL in the centr...

0 Tabish Rashid, et al. ∙

∙ 03/19/2020

Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

In many real-world settings, a team of agents must coordinate its behavi...

1 Tabish Rashid, et al. ∙

∙ 02/26/2020

Optimistic Exploration even with a Pessimistic Initialisation

Optimistic initialisation is an effective strategy for efficient explora...

5 Tabish Rashid, et al. ∙

∙ 10/16/2019

MAVEN: Multi-Agent Variational Exploration

Centralised training with decentralised execution is an important settin...

17 Anuj Mahajan, et al. ∙

∙ 06/05/2019

Exploration with Unreliable Intrinsic Reward in Multi-Agent Reinforcement Learning

This paper investigates the use of intrinsic reward to guide exploration...

14 Wendelin Böhmer, et al. ∙

∙ 02/11/2019

The StarCraft Multi-Agent Challenge

In the last few years, deep multi-agent reinforcement learning (RL) has ...

32 Mikayel Samvelyan, et al. ∙

∙ 03/30/2018

QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

In many real-world settings, a team of agents must coordinate their beha...

0 Tabish Rashid, et al. ∙

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