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Modeling the purposeful behavior of imperfect agents from a small number of observations is a challenging task. When restricted to the single-agent decision-theoretic setting, inverse optimal control techniques assume that observed behavior…

Computer Science and Game Theory · Computer Science 2013-08-19 Kevin Waugh , Brian D. Ziebart , J. Andrew Bagnell

Recent research in industrial organisation has investigated the essential place that middlemen have in the networks that make up our global economy. In this paper we attempt to understand how such middlemen compete with each other through a…

Computer Science and Game Theory · Computer Science 2013-10-15 Robert P. Gilles , Dimitrios Diamantaras

In physics, the wavefunctions of bosonic particles collapse when the system undergoes a Bose-Einstein condensation. In game theory, the strategy of an agent describes the probability to engage in a certain course of action. Strategies are…

Theoretical Economics · Economics 2022-07-06 Claudius Gros

Using the Minority Game model we study a broad spectrum of problems of market mechanism. We study the role of different types of agents: producers, speculators as well as noise traders. The central issue here is the information flow :…

Statistical Mechanics · Physics 2009-10-31 Damien Challet , Matteo Marsili , Yi-Cheng Zhang

The paper examines the learning mechanism of adaptive agents over weakly-connected graphs and reveals an interesting behavior on how information flows through such topologies. The results clarify how asymmetries in the exchange of data can…

Multiagent Systems · Computer Science 2015-12-08 Bicheng Ying , Ali H. Sayed

The general picture of game theoretic modeling dealt with here is characterized by a set of big players, also referred to as principals or major agents, acting on the background of large pools of small players, the impact of the behavior of…

Optimization and Control · Mathematics 2019-11-12 Vassili N. Kolokoltsov , Oleg A. Malafeyev

We consider open multi-agent systems. Unlike the systems usually studied in the literature, here agents may join or leave while the process studied takes place. The system composition and size evolve thus with time. We focus here on systems…

Multiagent Systems · Computer Science 2017-09-18 Julien M. Hendrickx , Samuel Martin

We consider a social system of interacting heterogeneous agents with learning abilities, a model close to Random Field Ising Models, where the random field corresponds to the idiosyncratic willingness to pay. Given a fixed price, agents…

Physics and Society · Physics 2009-11-13 Viktoriya Semeshenko , Mirta B. Gordon , Jean-Pierre Nadal

The dynamic behavior of a multiagent system in which the agent size $s_{i}$ is variable it is studied along a Lotka-Volterra approach. The agent size has hereby for meaning the fraction of a given market that an agent is able to capture…

Chaotic Dynamics · Physics 2012-09-04 L. F. Caram , C. F. Caiafa , A. N. Proto , M. Ausloos

We introduce the problem of adaptive self-organization in which the nodes of an anonymous, synchronous dynamic network must distributively change the collective distribution of their responses (or "colors") as a function of time-varying…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-30 Garrett Parzych , Joshua J. Daymude

We study the problem of agent selection in causal strategic learning under multiple decision makers and address two key challenges that come with it. Firstly, while much of prior work focuses on studying a fixed pool of agents that remains…

Artificial Intelligence · Computer Science 2024-02-06 Kiet Q. H. Vo , Muneeb Aadil , Siu Lun Chau , Krikamol Muandet

We present and discuss the results of an experimental analysis in the design of Boolean networks by means of genetic algorithms. A population of networks is evolved with the aim of finding a network such that the attractor it reaches is of…

Neural and Evolutionary Computing · Computer Science 2011-02-01 Andrea Roli , Cristian Arcaroli , Marco Lazzarini , Stefano Benedettini

We consider a model of Bayesian observational learning in which a sequence of agents receives a private signal about an underlying binary state of the world. Each agent makes a decision based on its own signal and its observations of…

Machine Learning · Computer Science 2025-04-29 Shuo Wu , Pawan Poojary , Randall Berry

In several network problems the optimum behavior of the agents (i.e., the nodes of the network) is not known before deployment. Furthermore, the agents might be required to adapt, i.e. change their behavior based on the environment…

Neural and Evolutionary Computing · Computer Science 2020-12-22 Anil Yaman , Giovanni Iacca

Complementarity is one of the main features underlying the interactions in biological and biochemical systems. Inspired by those systems we propose a model for the dynamical evolution of a system composed by agents that interact due to…

Disordered Systems and Neural Networks · Physics 2009-11-07 M. Copelli , R. M. Zorzenon dos Santos , J. S. Sa Martins

In a co-evolutionary context, the survive probability of individual elements of a system depends on their relation with their neighbors. The natural selection process depends on the whole population, which is determined by local events…

Biological Physics · Physics 2009-11-13 Juan G. Diaz Ochoa

We consider reallocation problems in settings where the initial endowment of each agent consists of a subset of the resources. The private information of the players is their value for every possible subset of the resources. The goal is to…

Computer Science and Game Theory · Computer Science 2014-04-29 Liad Blumrosen , Shahar Dobzinski

An analytical approach to network dynamics is used to show that when agents copy their state randomly the network arrives to a stationary status in which the distribution of states is independent of the agents degree. The effects of network…

Disordered Systems and Neural Networks · Physics 2009-11-10 Cesar A. Hidalgo , Francisco Claro , Pablo A. Marquet

In this work, we consider a population composed of a continuum of agents that seek to maximize a payoff function by moving on a network. The nodes in the network may represent physical locations or abstract choices. The population is…

Optimization and Control · Mathematics 2020-12-24 Nirabhra Mandal , Pavankumar Tallapragada

Generalization of the minority game to more than one market is considered. At each time step every agent chooses one of its strategies and acts on the market related to this strategy. If the payoff function allows for strong fluctuation of…

Trading and Market Microstructure · Quantitative Finance 2011-05-12 Karol Wawrzyniak , Wojciech Wislicki