Zobrazeno 1 - 10
of 2 493
pro vyhledávání: '"Martín, Carlos A."'
This paper presents an examination of State Space Models (SSM) and Koopman-based deep learning methods for modelling the dynamics of both linear and non-linear stiff strings. Through experiments with datasets generated under different initial conditi
Externí odkaz:
http://arxiv.org/abs/2408.16650
Autor:
Martin, Carlos, Sandholm, Tuomas
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, for example, when players' strategies are represented by the paramet
Externí odkaz:
http://arxiv.org/abs/2408.09306
Polar ice develops anisotropic crystal orientation fabrics under deformation, yet ice is most often modelled as an isotropic fluid. We present three-dimensional simulations of the crystal orientation fabric of Derwael Ice Rise including the surroundi
Externí odkaz:
http://arxiv.org/abs/2408.01069
Autor:
Martin, Carlos, Sandholm, Tuomas
Planning at execution time has been shown to dramatically improve performance for agents in both single-agent and multi-agent settings. A well-known family of approaches to planning at execution time are AlphaZero and its variants, which use Monte Ca
Externí odkaz:
http://arxiv.org/abs/2406.08687
Autor:
Martin, Carlos, Sandholm, Tuomas
We present a framework for computing approximate mixed-strategy Nash equilibria of continuous-action games. It is a modification of the traditional double oracle algorithm, extended to multiple players and continuous action spaces. Unlike prior metho
Externí odkaz:
http://arxiv.org/abs/2406.08683
Autor:
Ollero, Anibal, Suarez, Alejandro, Papaioannidis, Christos, Pitas, Ioannis, Marredo, Juan M., Duong, Viet, Ebeid, Emad, Kratky, Vit, Saska, Martin, Hanoune, Chloe, Afifi, Amr, Franchi, Antonio, Vourtsis, Charalampos, Floreano, Dario, Vasiljevic, Goran, Bogdan, Stjepan, Caballero, Alvaro, Ruggiero, Fabio, Lippiello, Vincenzo, Matilla, Carlos, Cioffi, Giovanni, Scaramuzza, Davide, Martinez-de-Dios, Jose R., Arrue, Begona C., Martin, Carlos, Zurad, Krzysztof, Gaitan, Carlos, Rodriguez, Jacob, Munoz, Antonio, Viguria, Antidio
Large-scale infrastructures are prone to deterioration due to age, environmental influences, and heavy usage. Ensuring their safety through regular inspections and maintenance is crucial to prevent incidents that can significantly affect public safet
Externí odkaz:
http://arxiv.org/abs/2401.02343
Autor:
Woodcock, Jim, Andersen, Mikkel Schmidt, Aranha, Diego F., Hallerstede, Stefan, Hansen, Simon Thrane, Jakobsen, Nikolaj Kuhne, Kulik, Tomas, Larsen, Peter Gorm, Macedo, Hugo Daniel, Martin, Carlos Ignacio Isasa, Norrild, Victor Alexander Mtsimbe
This report describes the state of the art in verifiable computation. The problem being solved is the following: The Verifiable Computation Problem (Verifiable Computing Problem) Suppose we have two computing agents. The first agent is the verifier,
Externí odkaz:
http://arxiv.org/abs/2308.15191
Autor:
Martin, Carlos, Sandholm, Tuomas
Search and planning algorithms have been a cornerstone of artificial intelligence since the field's inception. Giving reinforcement learning agents the ability to plan during execution time has resulted in significant performance improvements in vari
Externí odkaz:
http://arxiv.org/abs/2308.08693
Autor:
Martin, Carlos, Sandholm, Tuomas
There has been substantial progress on finding game-theoretic equilibria. Most of that work has focused on games with finite, discrete action spaces. However, many games involving space, time, money, and other fine-grained quantities have continuous
Externí odkaz:
http://arxiv.org/abs/2301.08830
Autor:
Martin, Carlos, Sandholm, Tuomas
We study the problem of computing an approximate Nash equilibrium of continuous-action game without access to gradients. Such game access is common in reinforcement learning settings, where the environment is typically treated as a black box. To tack
Externí odkaz:
http://arxiv.org/abs/2211.15936