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This paper investigates backdoor attack planning in stochastic control systems modeled as Markov Decision Processes (MDPs). A backdoor attack involves an adversary deploying a policy that performs well in the original MDP to pass testing,…

Systems and Control · Electrical Eng. & Systems 2026-04-27 Xinyi Wei , Shuo Han , Ahmed H. Hemida , Charles A. Kamhoua , Jie Fu

The paper studies the routing in the network shared by several users. Each user seeks to optimize either its own performance or some combination between its own performance and that of other users, by controlling the routing of its given…

Computer Science and Game Theory · Computer Science 2008-10-14 Amar Prakash Azad , Eitan Altman , R. El-Azouzi

Stochastic and soft optimal policies resulting from entropy-regularized Markov decision processes (ER-MDP) are desirable for exploration and imitation learning applications. Motivated by the fact that such policies are sensitive with…

Machine Learning · Computer Science 2022-01-03 Tien Mai , Patrick Jaillet

We study repeated games where players use an exponential learning scheme in order to adapt to an ever-changing environment. If the game's payoffs are subject to random perturbations, this scheme leads to a new stochastic version of the…

Probability · Mathematics 2010-10-22 Panayotis Mertikopoulos , Aris L. Moustakas

How is efficiency affected when demand excesses over supply are signalled through waiting in queues? We consider a class of congestion games with a nonatomic set of players of a constant mass, based on a formulation of generic linear…

Computer Science and Game Theory · Computer Science 2020-11-18 Costas Courcoubetis , Antonis Dimakis

Self-interested routing polices from individual users in a system can collectively lead to poor aggregate congestion in routing networks. The introduction of altruistic agents, whose goal is to benefit other agents in the system, can…

Computer Science and Game Theory · Computer Science 2024-04-12 Colton Hill , Philip N. Brown

We study nonzero-sum stochastic switching games. Two players compete for market dominance through controlling (via timing options) the discrete-state market regime $M$. Switching decisions are driven by a continuous stochastic factor $X$…

General Economics · Economics 2018-07-23 Liangchen Li , Michael Ludkovski

Many real-world decision problems involve the interaction of multiple self-interested agents with limited sensing ability. The partially observable stochastic game (POSG) provides a mathematical framework for modeling these problems,…

Computer Science and Game Theory · Computer Science 2024-10-30 Tyler Becker , Zachary Sunberg

We put forward a new model of congestion games where agents have uncertainty over the routes used by other agents. We take a non-probabilistic approach, assuming that each agent knows that the number of agents using an edge is within a…

Computer Science and Game Theory · Computer Science 2017-03-28 Reshef Meir , David Parkes

In this paper, the problem of smart grid energy management under stochastic dynamics is investigated. In the considered model, at the demand side, it is assumed that customers can act as prosumers who own renewable energy sources and can…

Computer Science and Game Theory · Computer Science 2017-08-08 Seyed Rasoul Etesami , Walid Saad , Narayan Mandayam , H. Vincent Poor

When reasoning about the strategic capabilities of an agent, it is important to consider the nature of its adversaries. In the particular context of controller synthesis for quantitative specifications, the usual problem is to devise a…

Computer Science and Game Theory · Computer Science 2014-04-04 Véronique Bruyère , Emmanuel Filiot , Mickael Randour , Jean-François Raskin

Stochastic games are an important class of problems that generalize Markov decision processes to game theoretic scenarios. We consider finite state two-player zero-sum stochastic games over an infinite time horizon with discounted rewards.…

Optimization and Control · Mathematics 2008-06-17 Parikshit Shah , Pablo A. Parrilo

Stochastic games generalize Markov decision processes (MDPs) to a multiagent setting by allowing the state transitions to depend jointly on all player actions, and having rewards determined by multiplayer matrix games at each state. We…

Computer Science and Game Theory · Computer Science 2013-01-18 Michael Kearns , Yishay Mansour , Satinder Singh

This paper studies the finite-time horizon Markov games where the agents' dynamics are decoupled but the rewards can possibly be coupled across agents. The policy class is restricted to local policies where agents make decisions using their…

Computer Science and Game Theory · Computer Science 2023-04-11 Runyu Zhang , Yuyang Zhang , Rohit Konda , Bryce Ferguson , Jason Marden , Na Li

In this paper, we consider discrete-time partially observed mean-field games with the risk-sensitive optimality criterion. We introduce risk-sensitivity behaviour for each agent via an exponential utility function. In the game model, each…

Systems and Control · Electrical Eng. & Systems 2022-11-11 Naci Saldi , Tamer Basar , Maxim Raginsky

Congestion games constitute an important class of non-cooperative games which was introduced by Rosenthal in 1973. In recent years, several extensions of these games were proposed to incorporate aspects that are not captured by the standard…

Computer Science and Game Theory · Computer Science 2017-01-27 Pieter Kleer , Guido Schäfer

We discuss and compare two methods of investigations for the asymptotic regime of stochastic differential games with a finite number of players as the number of players tends to the infinity. These two methods differ in the order in which…

Probability · Mathematics 2012-10-23 Rene Carmona , Francois Delarue , Aime Lachapelle

We consider a class of dynamic collective choice models with social interactions, whereby a large number of non-uniform agents have to individually settle on one of multiple discrete alternative choices, with the relevance of their would-be…

Systems and Control · Computer Science 2017-08-21 Rabih Salhab , Roland P. Malhamé , Jerome Le Ny

Strategic interaction in congested systems is commonly modelled using Stackelberg games, where competing leaders anticipate the behaviour of self-interested followers. A key limitation of existing models is that they typically ignore agents…

Multiagent Systems · Computer Science 2026-03-06 Niloofar Aminikalibar , Farzaneh Farhadi , Maria Chli

Most algorithmic studies on multi-agent information design so far have focused on the restricted situation with no inter-agent externalities; a few exceptions investigated truly strategic games such as zero-sum games and second-price…

Computer Science and Game Theory · Computer Science 2022-09-07 Chenghan Zhou , Thanh H. Nguyen , Haifeng Xu
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