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We consider the problem of learning by demonstration from agents acting in unknown stochastic Markov environments or games. Our aim is to estimate agent preferences in order to construct improved policies for the same task that the agents…

Machine Learning · Computer Science 2014-08-12 Aristide Tossou , Christos Dimitrakakis

We consider the problem of learning by demonstration from agents acting in unknown stochastic Markov environments or games. Our aim is to estimate agent preferences in order to construct improved policies for the same task that the agents…

Machine Learning · Statistics 2013-07-16 Aristide C. Y. Tossou , Christos Dimitrakakis

An agent choosing between various actions tends to take the one with the lowest cost. But this choice is arguably too rigid (not adaptive) to be useful in complex situations, e.g., where exploration-exploitation trade-off is relevant in…

Data Analysis, Statistics and Probability · Physics 2018-12-04 Armen E. Allahverdyan , Aram Galstyan , Ali E. Abbas , Zbigniew R. Struzik

We introduce a class of random mechanical systems called random billiards to study the problem of quantifying the irreversibility of nonequilibrium macroscopic systems. In a random billiard model, a point particle evolves by free motion…

Mathematical Physics · Physics 2021-01-11 Timothy Chumley , Renato Feres

We present a general framework for determining the power-efficiency trade-off relations across arbitrary thermal machines, addressing the lack of unified optimization results stemming from their diverse functionalities (e.g., heat engines,…

Statistical Mechanics · Physics 2025-11-20 Yu-Han Ma , Cong Fu

We develop a thermodynamic framework for modeling innovation adoption and abandonment dynamics using statistical mechanics. Starting from a mathematical model for an adoption distribution that fits empirically obtained date, we construct a…

Physics and Society · Physics 2026-04-21 Guilherme S. Y. Giardini , Carlo R. daCunha

The rheological behavior of soft glassy materials basically results from the interplay between shearing forces and an intrinsic slow dynamics. This competition can be described by a microscopic theory, which can be viewed as a…

Statistical Mechanics · Physics 2009-11-07 Ludovic Berthier

A significant roadblock to the development of principled multi-agent reinforcement learning is the fact that desired solution concepts like Nash equilibria may be intractable to compute. To overcome this obstacle, we take inspiration from…

Computer Science and Game Theory · Computer Science 2024-08-28 Eric Mazumdar , Kishan Panaganti , Laixi Shi

A system relying on the collective behavior of decision-makers can be vulnerable to a variety of adversarial attacks. How well can a system operator protect performance in the face of these risks? We frame this question in the context of…

Systems and Control · Electrical Eng. & Systems 2024-09-23 Keith Paarporn , Mahnoosh Alizadeh , Jason R. Marden

We consider a setting for Inverse Reinforcement Learning (IRL) where the learner is extended with the ability to actively select multiple environments, observing an agent's behavior on each environment. We first demonstrate that if the…

Artificial Intelligence · Computer Science 2016-01-26 Kareem Amin , Satinder Singh

Using methods of phenomenological non-equilibrium thermodynamics, the proof is performed that Jarzynski's equality is only valid in the reversible limit and that a conclusion to non-equilibrium inequalities concerning free energy and work…

Mathematical Physics · Physics 2013-07-02 Wolfgang Muschik

We discuss the thermoelectric (TE) transport in billiard systems of interacting particles, coupled to stochastic particle reservoirs. Recently in [1], analytical exact expressions for the TE transport of noninteracting gases of polyatomic…

Statistical Mechanics · Physics 2011-09-08 Giulio Casati , Carlos Mejia-Monasterio

Models of adaptive bet-hedging commonly adopt insights from Kelly's famous work on optimal gambling strategies and the financial value of information. In particular, such models seek evolutionary solutions that maximize long term average…

Populations and Evolution · Quantitative Biology 2020-03-18 Omri Tal , Tat Dat Tran

Winners-take-all situations introduce an incentive for agents to diversify their behavior, since doing so will result in splitting an eventual price with fewer people. At the same time, when the payoff of a process depends on a parameter…

Computer Science and Game Theory · Computer Science 2019-06-11 Abel Molina

The problem of the insensitivity of the macroscopic behavior of any thermodynamical system to partitioning generates a bias between the reproducibility of its macroscopic behavior viewed as the simplest form of causality and its long-term…

General Physics · Physics 2007-05-23 Maria K. Koleva

We consider a macroscopic system in contact with boundary reservoirs and/or under the action of an external field. We discuss the case in which the external forcing depends explicitly on time and drives the system from a nonequilibrium…

Statistical Mechanics · Physics 2015-06-05 L. Bertini , D. Gabrielli , G. Jona-Lasinio , C. Landim

Generalizing response theory of open systems far from equilibrium is a central quest of nonequilibrium statistical physics. Using stochastic thermodynamics, we develop an algebraic method to study the response of nonequilibrium steady state…

Statistical Mechanics · Physics 2023-08-09 Timur Aslyamov , Massimiliano Esposito

From a recent geometric generalization of Thermodynamic Uncertainty Relations (TURs) we derive novel upper bounds on the nonlinear response of an observable of an arbitrary system undergoing a change of probabilistic state. Various…

Statistical Mechanics · Physics 2022-03-09 Gianmaria Falasco , Massimiliano Esposito , Jean-Charles Delvenne

Master equation could be applied to model various kinds of biochemical systems. A general theory for its time-dependent nonequilibrium thermodynamics is rigorously derived. We not only introduce a concept of general internal energy, but…

Statistical Mechanics · Physics 2009-04-16 Hao Ge

We develop a game-theoretic framework for adversarially robust optimal safe predefined-time stabilization of parameter-dependent nonlinear dynamical systems with nonquadratic cost functionals. Our approach ensures that all system…

Optimization and Control · Mathematics 2025-11-20 Nick-Marios T. Kokolakis , Shanqing Liu , Jerome Darbon , Rahul Mangharam , George Em Karniadakis
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