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Acquiring a diverse repertoire of general-purpose skills remains an open challenge for robotics. In this work, we propose self-supervising control on top of human teleoperated play data as a way to scale up skill learning. Play has two…

Robotics · Computer Science 2019-12-23 Corey Lynch , Mohi Khansari , Ted Xiao , Vikash Kumar , Jonathan Tompson , Sergey Levine , Pierre Sermanet

This article deals with classes of antagonistic games with two players. A game is specified in terms of two `hostile' stochastic processes representing mutual attacks upon random times exerting casualties of random magnitudes. The game ends…

Probability · Mathematics 2019-01-23 J. H. Dshalalow , K. Iwezulu , R. T. White

We consider a subclass of $n$-player stochastic games, in which players have their own internal state/action spaces while they are coupled through their payoff functions. It is assumed that players' internal chains are driven by independent…

Machine Learning · Computer Science 2023-03-23 S. Rasoul Etesami

We study the effects of individual perceptions of payoffs in two-player games. In particular we consider the setting in which individuals' perceptions of the game are influenced by their previous experiences and outcomes. Accordingly, we…

Computer Science and Game Theory · Computer Science 2019-06-05 Alberto Antonioni , Luis A. Martinez-Vaquero , Cole Mathis , Leto Peel , Massimo Stella

This paper considers the discounted criterion of nonzero-sum decentralized stochastic games with prospect players. The state and action spaces are finite. The state transition probability is nonstationary. Each player independently controls…

Optimization and Control · Mathematics 2024-05-16 Yiting Wu , Junyu Zhang

We propose the concept of a Lagrangian game to solve constrained Markov games. Such games model scenarios where agents face cost constraints in addition to their individual rewards, that depend on both agent joint actions and the evolving…

Optimization and Control · Mathematics 2025-03-14 Soham Das , Santiago Paternain , Luiz F. O. Chamon , Ceyhun Eksin

Certain but important classes of strategic-form games, including zero-sum and identical-interest games, have the fictitious-play-property (FPP), i.e., beliefs formed in fictitious play dynamics always converge to a Nash equilibrium (NE) in…

Computer Science and Game Theory · Computer Science 2022-05-24 Muhammed O. Sayin , Kaiqing Zhang , Asuman Ozdaglar

This paper is concerned with a linear-quadratic (LQ) leader-follower differential game with mixed deterministic and stochastic controls. In the game, the follower is a random controller which means that the follower can choose adapted…

Optimization and Control · Mathematics 2025-09-26 Jingtao Shi , Guangchen Wang

A simple model for cooperation between "selfish" agents, which play an extended version of the Prisoner's Dilemma(PD) game, in which they use arbitrary payoffs, is presented and studied. A continuous variable, representing the probability…

Condensed Matter · Physics 2009-11-10 H. Fort

We study a zero-sum stochastic differential game (SDG) in which one controller plays an impulse control while their opponent plays a stochastic control. We consider an asymmetric setting in which the impulse player commits to, at the start…

Probability · Mathematics 2019-01-31 Parsiad Azimzadeh

Probabilistic model checking for stochastic games enables formal verification of systems that comprise competing or collaborating entities operating in a stochastic environment. Despite good progress in the area, existing approaches focus…

Logic in Computer Science · Computer Science 2019-07-09 Marta Kwiatkowska , Gethin Norman , David Parker , Gabriel Santos

We study a two-player Stackelberg game with incomplete information such that the follower's strategy belongs to a known family of parameterized functions with an unknown parameter vector. We design an adaptive learning approach to…

Computer Science and Game Theory · Computer Science 2021-01-12 Guosong Yang , Radha Poovendran , João P. Hespanha

Piecewise Deterministic Markov Processes (PDMPs) are studied in a general framework. First, different constructions are proven to be equivalent. Second, we introduce a coupling between two PDMPs following the same differential flow which…

Probability · Mathematics 2021-08-03 Alain Durmus , Arnaud Guillin , Pierre Monmarché

This paper extends the framework of partially observable Markov decision processes (POMDPs) to multi-agent settings by incorporating the notion of agent models into the state space. Agents maintain beliefs over physical states of the…

Artificial Intelligence · Computer Science 2011-09-13 P. Doshi , P. J. Gmytrasiewicz

Multi-agent planning under stochastic dynamics is usually formalised using decentralized (partially observable) Markov decision processes ( MDPs) and reachability or expected reward specifications. In this paper, we propose a different…

Logic in Computer Science · Computer Science 2025-02-20 Francesco Pontiggia , Filip Macák , Roman Andriushchenko , Michele Chiari , Milan Češka

Two-player win/lose games of infinite duration are involved in several disciplines including computer science and logic. If such a game has deterministic winning strategies, one may ask how simple such strategies can get. The answer may…

Computer Science and Game Theory · Computer Science 2020-02-04 Stéphane Le Roux

Adversarial decision-making in partially observable multi-agent systems requires sophisticated strategies for both deception and counter-deception. This paper presents a sequential hypothesis testing (SHT)-driven framework that captures the…

Optimization and Control · Mathematics 2026-04-14 Haosheng Zhou , Daniel Ralston , Xu Yang , Ruimeng Hu

In a Stackelberg game, a leader commits to a randomized strategy, and a follower chooses their best strategy in response. We consider an extension of a standard Stackelberg game, called a discrete-time dynamic Stackelberg game, that has an…

Computer Science and Game Theory · Computer Science 2022-02-11 Niklas Lauffer , Mahsa Ghasemi , Abolfazl Hashemi , Yagiz Savas , Ufuk Topcu

This paper studies a class of strongly monotone games involving non-cooperative agents that optimize their own time-varying cost functions. We assume that the agents can observe other agents' historical actions and choose actions that best…

Optimization and Control · Mathematics 2023-09-04 Zifan Wang , Yi Shen , Michael M. Zavlanos , Karl H. Johansson

In this paper we establish a new connection between a class of 2-player nonzero-sum games of optimal stopping and certain $2$-player nonzero-sum games of singular control. We show that whenever a Nash equilibrium in the game of stopping is…

Optimization and Control · Mathematics 2017-12-29 Tiziano De Angelis , Giorgio Ferrari
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