145 citations · 145 across the 15 of their papers we have counts for
17 papers
On the LLM Verification for Argument Graph Generation
Jakub Bąba, Jarosław A. Chudziak
Multi-agent LLM systems can formalize natural-language argumentation end-to-end, turning plain text into structured graphs by classifying components, connecting them with relations…
Regularized policy gradient with learned mixtures of Gaussians for games with continuous actions
Ondřej Kubíček, Viliam Lisý, Tuomas Sandholm
Most successes of superhuman game-playing algorithms are in games with discrete actions, yet in auctions, robotics, sports, or trading, actions are nearly continuous. Prior techniq…
Test-time Reinforcement Learning in Imperfect Information Games
Ondrej Kubicek, Viliam Lisy, Tuomas Sandholm
Test-time reasoning has significantly improved performance in domains ranging from games to language models. However, test-time policy changes with formal guarantees on the perform…
Watermarked Game Solving via Perturbed Regret Minimization
Juho Kim, Tuomas Sandholm
Many real-world interactions among self-interested parties can be modeled by game theory, and the rapid advancements in AI have raised concerns about the possible misuse---accident…
On the Complexity of Correlated Equilibria Beyond Normal-Form Games
Ioannis Anagnostides, Constantinos Daskalakis, Gabriele Farina +3
Correlated equilibria are a fundamental solution concept in game theory. However, despite decades of research, the complexity beyond games of polynomial type -- such as extensive-f…
Domain-Independent Game Abstraction using Word Embedding Techniques
Juho Kim, Tuomas Sandholm
Many games of interest in the real world are often intractably large, thereby necessitating the use of game abstraction to shrink them in size, typically by many magnitudes. Over t…
Watermarking Game-Playing Agents in Perfect-Information Extensive-Form Games
Juho Kim, Fei Fang, Tuomas Sandholm
Watermarking techniques for large language models (LLMs), which encode hidden information in the output so its source can be verified, have gained significant attention in recent d…
Parallelizing Counterfactual Regret Minimization
Juho Kim, Tuomas Sandholm
Parallelization has played an instrumental role in the field of artificial intelligence (AI), drastically reducing the time taken to train and evaluate large AI models. In contrast…
Heuristic Pathologies and Further Variance Reduction via Uncertainty Propagation in the AIVAT Family of Techniques
Juho Kim, Tuomas Sandholm
How should an agent's performance in a multiagent environment be evaluated when there is a limited sample size or a high cost of running a trial? The AIVAT family of variance reduc…
General search techniques without common knowledge for imperfect-information games, and application to superhuman Fog of War chess
Brian Hu Zhang, Tuomas Sandholm
Since the advent of AI, games have served as progress benchmarks. Meanwhile, imperfect-information variants of chess have existed for over a century, present extreme challenges, an…
Learning a Game by Paying the Agents
Brian Hu Zhang, Tao Lin, Yiling Chen +1
We study the problem of learning the utility functions of no-regret learning agents in a repeated normal-form game. Differing from most prior literature, we introduce a principal w…
A Multiagent Path Search Algorithm for Large-Scale Coalition Structure Generation
Redha Taguelmimt, Samir Aknine, Djamila Boukredera +2
Coalition structure generation (CSG), i.e. the problem of optimally partitioning a set of agents into coalitions to maximize social welfare, is a fundamental computational problem…
Solving Infinite-Player Games with Player-to-Strategy Networks
Carlos Martin, Tuomas Sandholm
We present a new approach to solving games with a countably or uncountably infinite number of players. Such games are often used to model multiagent systems with a large number of…
On the Power of Perturbation under Sampling in Solving Extensive-Form Games
Wataru Masaka, Mitsuki Sakamoto, Kenshi Abe +3
We investigate how perturbation does and does not improve the Follow-the-Regularized-Leader (FTRL) algorithm in solving imperfect-information extensive-form games under sampling, w…
Joint-perturbation simultaneous pseudo-gradient
Carlos Martin, Tuomas Sandholm
We study the problem of computing an approximate Nash equilibrium of a game whose strategy space is continuous without access to gradients of the utility function. Such games arise…
Faster Optimal Coalition Structure Generation via Offline Coalition Selection and Graph-Based Search
Redha Taguelmimt, Samir Aknine, Djamila Boukredera +2
Coalition formation is a key capability in multi-agent systems. An important problem in coalition formation is coalition structure generation: partitioning agents into coalitions t…
Game-Theoretic Multiagent Reinforcement Learning
Yaodong Yang, Chengdong Ma, Zihan Ding +4
Tremendous advances have been made in multiagent reinforcement learning (MARL). MARL corresponds to the learning problem in a multiagent system in which multiple agents learn simul…