Tabish Rashid

According to our database, Tabish Rashid authored at least 15 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Visual Encoders for Data-Efficient Imitation Learning in Modern Video Games.

Lukas Schäfer, Logan Jones, Anssi Kanervisto, Yuhan Cao, Tabish Rashid, Raluca Georgescu, David Bignell, Siddhartha Sen, Andrea Treviño Gavito, Sam Devlin

CoRR, 2023

Imitating Human Behaviour with Diffusion Models.

Tim Pearce, Tabish Rashid, Anssi Kanervisto, David Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2021

Softmax with Regularization: Better Value Estimation in Multi-Agent Reinforcement Learning.

Ling Pan, Tabish Rashid, Bei Peng, Longbo Huang, Shimon Whiteson

CoRR, 2021

FACMAC: Factored Multi-Agent Centralised Policy Gradients.

Bei Peng, Tabish Rashid, Christian Schröder de Witt, Pierre-Alexandre Kamienny, Philip H. S. Torr, Wendelin Boehmer, Shimon Whiteson

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Regularized Softmax Deep Multi-Agent Q-Learning.

Ling Pan, Tabish Rashid, Bei Peng, Longbo Huang, Shimon Whiteson

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Estimating α-Rank by Maximizing Information Gain.

Tabish Rashid, Cheng Zhang, Kamil Ciosek

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning.

Tabish Rashid, Mikayel Samvelyan, Christian Schröder de Witt, Gregory Farquhar, Jakob N. Foerster, Shimon Whiteson

J. Mach. Learn. Res., 2020

Weighted QMIX: Expanding Monotonic Value Function Factorisation.

Tabish Rashid, Gregory Farquhar, Bei Peng, Shimon Whiteson

CoRR, 2020

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

Tabish Rashid, Gregory Farquhar, Bei Peng, Shimon Whiteson

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Optimistic Exploration even with a Pessimistic Initialisation.

Tabish Rashid, Bei Peng, Wendelin Boehmer, Shimon Whiteson

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Exploration with Unreliable Intrinsic Reward in Multi-Agent Reinforcement Learning.

Wendelin Böhmer, Tabish Rashid, Shimon Whiteson

CoRR, 2019

MAVEN: Multi-Agent Variational Exploration.

Anuj Mahajan, Tabish Rashid, Mikayel Samvelyan, Shimon Whiteson

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

The StarCraft Multi-Agent Challenge.

Mikayel Samvelyan, Tabish Rashid, Christian Schröder de Witt, Gregory Farquhar, Nantas Nardelli, Tim G. J. Rudner, Chia-Man Hung, Philip H. S. Torr, Jakob N. Foerster, Shimon Whiteson

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018

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

Tabish Rashid, Mikayel Samvelyan, Christian Schröder de Witt, Gregory Farquhar, Jakob N. Foerster, Shimon Whiteson

Proceedings of the 35th International Conference on Machine Learning, 2018

2016

A New Take on Detecting Insider Threats: Exploring the Use of Hidden Markov Models.

Tabish Rashid, Ioannis Agrafiotis, Jason R. C. Nurse

Proceedings of the 8th ACM CCS International Workshop on Managing Insider Security Threats, 2016