DH

Daniel Hennes

0000-0002-3646-5286

cs.AIcs.MAcs.LGcs.GTstat.MLcs.ROFootballphysics.space-phSoccerArtificial Intelligence

On Valency

published · living versions

Designing Complex Interplanetary Trajectories for the Global Trajectory Optimization Competitions

with Dario Izzo, Luís F. Simões, Marcus Märtens

1 version

W_c833heabv1 · current

Preprints & journals

27 papers in the corpus · 2015–2026

Modular Discovery of General Game-Playing Algorithms with Large Language Models

Zun Li, John Schultz, Marc Lanctot et al.

0 citations

2609.33115v12026arXiv

Game Arena: Strategic LLM Evaluation in Competitive Environments

Bovard Doerschuk-Tiberi, Yao Yan, Justin Chiu et al.

0 citations

2609.31473v12026arXiv

Code-Space Response Oracles: Generating Interpretable Multi-Agent Policies with Large Language Models

Daniel Hennes, Zun Li, John Schultz et al.

0 citations

2603.10098v12026arXiv

Discovering Multiagent Learning Algorithms with Large Language Models

Zun Li, John Schultz, Daniel Hennes et al.

0 citations

2602.16928v32026arXiv

Code World Models for General Game Playing

Wolfgang Lehrach, Daniel Hennes, Miguel Lazaro-Gredilla et al.

0 citations

2510.04542v12025arXiv

Mastering Board Games by External and Internal Planning with Language Models

John Schultz, Jakub Adamek, Matej Jusup et al.

2 citations

2412.12119v32024arXiv

TacticAI: an AI assistant for football tactics.

Wang, Zhe, Veličković, Petar, Hennes, Daniel et al.

91 citations

385037742024Nature communications. 2024;15(1):1906

Approximating the Core via Iterative Coalition Sampling

Ian Gemp, Marc Lanctot, Luke Marris et al.

1 citation

2402.03928v12024arXiv

Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning

Marc Lanctot, John Schultz, Neil Burch et al.

3 citations

2303.03196v22023arXiv

Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning

Zun Li, Marc Lanctot, Kevin R. McKee et al.

1 citation

2302.00797v42023Proc. 34th Int. Joint Conf. Artif. Intell. (IJCAI 2025), pp. 161-169

Mastering the game of Stratego with model-free multiagent reinforcement learning.

Perolat, Julien, De Vylder, Bart, Hennes, Daniel et al.

160 citations

364548472022Science (New York, N.Y.). 2022;378(6623):990-996

Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments

Ian Gemp, Thomas Anthony, Yoram Bachrach et al.

3 citations

2209.10958v12022arXiv

From motor control to team play in simulated humanoid football.

Liu, Siqi, Lever, Guy, Wang, Zhe et al.

88 citations

360445562022Science robotics. 2022;7(69):eabo0235

Multiagent off-screen behavior prediction in football.

Omidshafiei, Shayegan, Hennes, Daniel, Garnelo, Marta et al.

26 citations

356064002022Scientific reports. 2022;12(1):8638

NeuPL: Neural Population Learning

Siqi Liu, Luke Marris, Daniel Hennes et al.

2 citations

2202.07415v12022arXiv

Which priors matter? Benchmarking models for learning latent dynamics

Aleksandar Botev, Andrew Jaegle, Peter Wirnsberger et al.

9 citations

2111.05458v12021arXiv

Evolutionary Dynamics and $\Phi$ -Regret Minimization in Games

Georgios Piliouras, Mark Rowland, Shayegan Omidshafiei et al.

3 citations

2106.14668v12021arXiv

Time-series Imputation of Temporally-occluded Multiagent Trajectories

Shayegan Omidshafiei, Daniel Hennes, Marta Garnelo et al.

2 citations

2106.04219v12021arXiv

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

Karl Tuyls, Shayegan Omidshafiei, Paul Muller et al.

116 citations

2011.09192v12020arXiv

Navigating the landscape of multiplayer games.

Omidshafiei, Shayegan, Tuyls, Karl, Czarnecki, Wojciech M et al.

28 citations

331543622020Nature communications. 2020;11(1):5603

A Generalized Training Approach for Multiagent Learning

Paul Muller, Shayegan Omidshafiei, Mark Rowland et al.

49 citations

1909.12823v22019arXiv

OpenSpiel: A Framework for Reinforcement Learning in Games

Marc Lanctot, Edward Lockhart, Jean-Baptiste Lespiau et al.

103 citations

1908.09453v62019arXiv

Neural Replicator Dynamics

Daniel Hennes, Dustin Morrill, Shayegan Omidshafiei et al.

11 citations

1906.00190v52019arXiv

A Note on the Depth-from-Defocus Mechanism of Jumping Spiders.

Nolte, Aleke, Hennes, Daniel, Izzo, Dario et al.

2 citations

311051662020Biomimetics (Basel, Switzerland). 2017;2(1)

Persistent self-supervised learning principle: from stereo to monocular vision for obstacle avoidance

Kevin van Hecke, Guido de Croon, Laurens van der Maaten et al.

4 citations

1603.08047v12016arXiv

GTOC8: Results and Methods of ESA Advanced Concepts Team and JAXA-ISAS

Dario Izzo, Daniel Hennes, Marcus Martens et al.

1 citation

1602.00849v22016arXiv

Designing Complex Interplanetary Trajectories for the Global Trajectory Optimization Competitions

Dario Izzo, Daniel Hennes, Lu'is F. Simoes et al.

43 citations

1511.00821v32015arXiv

Career total: 117 works. 27 are in this corpus.

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