Random Irregular Block-hierarchical Networks: Algorithms for Computation of Main Properties. - Mikayel Samvelyan; Svetlana Avetisyan (CoRR, 2015)

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 (ICML, 2018)

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 (AAMAS, 2019)

MAVEN: Multi-Agent Variational Exploration. - Anuj Mahajan; Tabish Rashid; Mikayel Samvelyan; Shimon Whiteson (NeurIPS, 2019)

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)

Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning. - Anuj Mahajan; Mikayel Samvelyan; Lei Mao; Viktor Makoviychuk; Animesh Garg; Jean Kossaifi; Shimon Whiteson; Yuke Zhu; Animashree Anandkumar (ICML, 2021)

Insights From the NeurIPS 2021 NetHack Challenge. - Eric Hambro; Sharada P. Mohanty; Dmitrii Babaev; Minwoo Byeon; Dipam Chakraborty; Edward Grefenstette; Minqi Jiang; DaeJin Jo; Anssi Kanervisto; Jongmin Kim 006; Sungwoong Kim; Robert Kirk; et al. (NeurIPS (Competition and Demos), 2021)

MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research. - Mikayel Samvelyan; Robert Kirk; Vitaly Kurin; Jack Parker-Holder; Minqi Jiang; Eric Hambro; Fabio Petroni; Heinrich Küttler; Edward Grefenstette; Tim Rocktäschel (NeurIPS Datasets and Benchmarks, 2021)

Reinforcement Learning in Factored Action Spaces using Tensor Decompositions. - Anuj Mahajan; Mikayel Samvelyan; Lei Mao; Viktor Makoviychuk; Animesh Garg; Jean Kossaifi; Shimon Whiteson; Yuke Zhu; Animashree Anandkumar (CoRR, 2021)

Hierarchical Kickstarting for Skill Transfer in Reinforcement Learning. - Michael T. Matthews; Mikayel Samvelyan; Jack Parker-Holder; Edward Grefenstette; Tim Rocktäschel (CoLLAs, 2022)

Evolving Curricula with Regret-Based Environment Design. - Jack Parker-Holder; Minqi Jiang; Michael Dennis 001; Mikayel Samvelyan; Jakob N. Foerster; Edward Grefenstette; Tim Rocktäschel (ICML, 2022)

GriddlyJS: A Web IDE for Reinforcement Learning. - Christopher Bamford 001; Minqi Jiang; Mikayel Samvelyan; Tim Rocktäschel (NeurIPS, 2022)

Generalization in Cooperative Multi-Agent Systems. - Anuj Mahajan; Mikayel Samvelyan; Tarun Gupta 002; Benjamin Ellis; Mingfei Sun 001; Tim Rocktäschel; Shimon Whiteson (CoRR, 2022)

SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning. - Benjamin Ellis; Skander Moalla; Mikayel Samvelyan; Mingfei Sun 001; Anuj Mahajan; Jakob N. Foerster; Shimon Whiteson (CoRR, 2022)

MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning. - Mikayel Samvelyan; Akbir Khan; Michael Dennis 001; Minqi Jiang; Jack Parker-Holder; Jakob Nicolaus Foerster; Roberta Raileanu; Tim Rocktäschel (ICLR, 2023)

SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning. - Benjamin Ellis; Jonathan Cook 004; Skander Moalla; Mikayel Samvelyan; Mingfei Sun 001; Anuj Mahajan; Jakob N. Foerster; Shimon Whiteson (NeurIPS, 2023)

Mix-ME: Quality-Diversity for Multi-Agent Learning. - Garðar Ingvarsson; Mikayel Samvelyan; Bryan Lim; Manon Flageat; Antoine Cully; Tim Rocktäschel (CoRR, 2023)

JaxMARL: Multi-Agent RL Environments in JAX. - Alexander Rutherford; Benjamin Ellis; Matteo Gallici; Jonathan Cook 004; Andrei Lupu; Garðar Ingvarsson; Timon Willi; Akbir Khan; Christian Schröder de Witt; Alexandra Souly; Saptarashmi Bandyopadhyay; Mikayel Samvelyan; et al. (CoRR, 2023)

JaxMARL: Multi-Agent RL Environments and Algorithms in JAX. - Alexander Rutherford; Benjamin Ellis; Matteo Gallici; Jonathan Cook 004; Andrei Lupu; Garðar Ingvarsson; Timon Willi; Akbir Khan; Christian Schröder de Witt; Alexandra Souly; Saptarashmi Bandyopadhyay; Mikayel Samvelyan; et al. (AAMAS, 2024)

Multi-Agent Diagnostics for Robustness via Illuminated Diversity. - Mikayel Samvelyan; Davide Paglieri; Minqi Jiang; Jack Parker-Holder; Tim Rocktäschel (AAMAS, 2024)

Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning. - Michael T. Matthews; Michael Beukman; Benjamin Ellis; Mikayel Samvelyan; Matthew Thomas Jackson; Samuel Coward; Jakob Nicolaus Foerster (ICML, 2024)

JaxMARL: Multi-Agent RL Environments and Algorithms in JAX. - Alexander Rutherford; Benjamin Ellis; Matteo Gallici; Jonathan Cook 004; Andrei Lupu; Garðar Ingvarsson; Timon Willi; Ravi Hammond; Akbir Khan; Christian Schröder de Witt; Alexandra Souly; Saptarashmi Bandyopadhyay; et al. (NeurIPS, 2024)

Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts. - Mikayel Samvelyan; Sharath Chandra Raparthy; Andrei Lupu; Eric Hambro; Aram H. Markosyan; Manish Bhatt; Yuning Mao; Minqi Jiang; Jack Parker-Holder; Jakob N. Foerster; Tim Rocktäschel; Roberta Raileanu (NeurIPS, 2024)

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms. - Alex Havrilla; Edward Hughes 001; Mikayel Samvelyan; Jacob D. Abernethy (CoRR, 2025)