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We consider the problem of creating assistants that can help agents solve new sequential decision problems, assuming the agent is not able to specify the reward function explicitly to the assistant. Instead of acting in place of the agent…

Machine Learning · Computer Science 2022-12-01 Sebastiaan De Peuter , Samuel Kaski

We study the evolution of cooperation in the prisoner's dilemma game, whereby a coevolutionary rule is introduced that molds the random topology of the interaction network in two ways. First, existing links are deleted whenever a player…

Physics and Society · Physics 2009-09-25 Attila Szolnoki , Matjaz Perc

A new approach for the study of social games and communications is proposed. Games are simulated between cognitive players who build the opponent's internal model and decide their next strategy from predictions based on the model. In this…

adap-org · Physics 2009-10-30 Makoto Taiji , Takashi Ikegami

We study a spatial two-strategy (cooperation and defection) Prisoner's Dilemma game with two types ($A$ and $B$) of players located on the sites of a square lattice. The evolution of strategy distribution is governed by iterated strategy…

Physics and Society · Physics 2009-01-15 Gyorgy Szabo , Attila Szolnoki

Scenario decision making offers a flexible way of making decision in an uncertain environment while obtaining probabilistic guarantees on the risk of failure of the decision. The idea of this approach is to draw samples of the uncertainty…

Optimization and Control · Mathematics 2025-09-03 Guillaume O. Berger

To achieve common goals, we often use joint commitments. Our commitment helps us to coordinate with our partners and assures them that their cooperative efforts will benefit themselves. However, if one of us can exploit the other's…

Computer Science and Game Theory · Computer Science 2025-02-20 Marcus Krellner , The Anh Han

Epstein introduced an agent-based model called Demographic Prisoner's dilemma. He shows, via simulations, that cooperation in this spatial evolutionary repeated game can be sustained. In order to do proves, we put on this model a particle…

Probability · Mathematics 2016-09-22 Sylvain Gibaud

This paper aims to put forward the concept that learning to take safe actions in unknown environments, even with probability one guarantees, can be achieved without the need for an unbounded number of exploratory trials, provided that one…

Machine Learning · Computer Science 2021-04-01 Agustin Castellano , Juan Bazerque , Enrique Mallada

This work considers a repeated principal-agent bandit game, where the principal can only interact with her environment through the agent. The principal and the agent have misaligned objectives and the choice of action is only left to the…

We focus on the heterogeneity of social networks and its role to the emergence of prevailing cooperation and sustaining cooperators. The social networks are representative of the interaction relationships between players and their…

Dynamical Systems · Mathematics 2009-11-11 Feng Fu , Lianghuan Liu , Long Wang

With the development of artificial intelligence, human beings are increasingly interested in human-agent collaboration, which generates a series of problems about the relationship between agents and humans, such as trust and cooperation.…

Physics and Society · Physics 2025-04-30 Danyang Jia , Xiangfeng Dai , Junliang Xing , Pin Tao , Yuanchun Shi , Zhen Wang

The Iterated Prisoner's Dilemma (IPD) is a well studied framework for understanding direct reciprocity and cooperation in pairwise encounters. However, measuring the morality of various IPD strategies is still largely lacking. Here, we…

Physics and Society · Physics 2023-02-28 Grant Molnar , Caroline Hammond , Feng Fu

We study the evolution of behavior under reinforcement learning in a Prisoner's Dilemma where agents interact in a regular network and can learn about whether they play one-shot or repeatedly by incurring a cost of deliberation. With…

Physics and Society · Physics 2024-03-28 Rossana Mastrandrea , Leonardo Boncinelli , Ennio Bilancini

We explore a collaborative and cooperative multi-agent reinforcement learning setting where a team of reinforcement learning agents attempt to solve a single cooperative task in a multi-scenario setting. We propose a novel multi-agent…

Multiagent Systems · Computer Science 2019-08-27 Hassam Ullah Sheikh , Ladislau Bölöni

We consider the coupled dynamics of the adaption of network structure and the evolution of strategies played by individuals occupying the network vertices. We propose a computational model in which each agent plays a $n$-round Prisoner's…

Physics and Society · Physics 2007-11-05 Feng Fu , Xiaojie Chen , Lianghuan Liu , Long Wang

A checkers-like model game with a simplified set of rules is studied through extensive simulations of agents with different expertise and strategies. The introduction of complementary strategies, in a quite general way, provides a tool to…

Artificial Intelligence · Computer Science 2016-08-26 J. Quetzalcóatl Toledo-Marín , Rogelio Díaz-Méndez , Marcelo del Castillo Mussot

Cooperation is fundamental in Multi-Agent Systems (MAS) and Multi-Agent Reinforcement Learning (MARL), often requiring agents to balance individual gains with collective rewards. In this regard, this paper aims to investigate strategies to…

Computer Science and Game Theory · Computer Science 2024-05-06 Vaigarai Sathi , Sabahat Shaik , Jaswanth Nidamanuri

We consider a network of coupled agents playing the Prisoner's Dilemma game, in which players are allowed to pick a strategy in the interval [0,1], with 0 corresponding to defection, 1 to cooperation, and intermediate values representing…

Adaptation and Self-Organizing Systems · Physics 2015-05-28 Francesco Sorrentino , Nicholas Mecholsky

Is there a canonical way to think of agency beyond reward maximisation? In this paper, we show that any type of behaviour complying with physically sound assumptions about how macroscopic biological agents interact with the world…

Artificial Intelligence · Computer Science 2024-01-24 Lancelot Da Costa , Samuel Tenka , Dominic Zhao , Noor Sajid

Social dilemmas are situations where individuals face a temptation to increase their payoffs at a cost to total welfare. Building artificially intelligent agents that achieve good outcomes in these situations is important because many real…

Artificial Intelligence · Computer Science 2018-03-05 Adam Lerer , Alexander Peysakhovich
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