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Rewarding cooperation is in many ways expected behaviour from social players. However, strategies that promote antisocial behaviour are also surprisingly common, not just in human societies, but also among eusocial insects and bacteria.…

Populations and Evolution · Quantitative Biology 2015-10-30 Attila Szolnoki , Matjaz Perc

We propose a novel formulation for approximating reachable sets through a minimum discounted reward optimal control problem. The formulation yields a continuous solution that can be obtained by solving a Hamilton-Jacobi equation.…

Optimization and Control · Mathematics 2018-09-05 Anayo K. Akametalu , Shromona Ghosh , Jaime F. Fisac , Claire J. Tomlin

Social dilemmas have been widely studied to explain how humans are able to cooperate in society. Considerable effort has been invested in designing artificial agents for social dilemmas that incorporate explicit agent motivations that are…

Multiagent Systems · Computer Science 2021-08-30 Nicolas Anastassacos , Stephen Hailes , Mirco Musolesi

Mixed incentives among a population with multiagent teams has been shown to have advantages over a fully cooperative system; however, discovering the best mixture of incentives or team structure is a difficult and dynamic problem. We…

Artificial Intelligence · Computer Science 2023-04-18 David Radke , Kyle Tilbury

This paper studies optimal Public Private Partnerships contract between a public entity and a consortium, in continuous-time and with a continuous payment, with the possibility for the public to stop the contract. The public ("she") pays a…

Probability · Mathematics 2022-10-28 Ishak Hajjej , Caroline Hillairet , Mohamed Mnif

Whether a population of decision-making individuals will reach a state of satisfactory decisions is a fundamental problem in studying collective behaviors. In the framework of evolutionary game theory and by means of potential functions,…

Multiagent Systems · Computer Science 2022-01-13 Negar Sakhaei , Zeinab Maleki , Pouria Ramazi

Coordination is often critical to forming prosocial behaviors -- behaviors that increase the overall sum of rewards received by all agents in a multi-agent game. However, state of the art reinforcement learning algorithms often suffer from…

Multiagent Systems · Computer Science 2021-05-17 Woodrow Z. Wang , Mark Beliaev , Erdem Bıyık , Daniel A. Lazar , Ramtin Pedarsani , Dorsa Sadigh

Monitoring with implicated punishment is common in human societies to avert freeriding on common goods. But is it effective in promoting public cooperation? We show that the introduction of monitoring and implicated punishment is indeed…

Populations and Evolution · Quantitative Biology 2015-11-20 Xiaojie Chen , Tatsuya Sasaki , Matjaz Perc

We consider the problem of learning control policies that optimize a reward function while satisfying constraints due to considerations of safety, fairness, or other costs. We propose a new algorithm, Projection-Based Constrained Policy…

Machine Learning · Computer Science 2020-10-08 Tsung-Yen Yang , Justinian Rosca , Karthik Narasimhan , Peter J. Ramadge

Prosocial punishment has been proved to be a powerful mean to promote cooperation. Recent studies have found that social exclusion, which indeed can be regarded as a kind of punishment, can also support cooperation. However, if prosocial…

Physics and Society · Physics 2017-05-09 Linjie Liu , Xiaojie Chen , Attila Szolnoki

In this paper we address the cooperation problem in structured populations by considering the prisoner's dilemma game as metaphor of the social interactions between individuals with imitation capacity. We present a new strategy update rule…

Computer Science and Game Theory · Computer Science 2013-03-19 Ignacio Gomez Portillo

Classification algorithms are increasingly used in areas such as housing, credit, and law enforcement in order to make decisions affecting peoples' lives. These algorithms can change individual behavior deliberately (a fraud prediction…

Theoretical Economics · Economics 2023-07-06 Elizabeth Maggie Penn , John W. Patty

Reinforcement learning offers the promise of automating the acquisition of complex behavioral skills. However, compared to commonly used and well-understood supervised learning methods, reinforcement learning algorithms can be brittle,…

Machine Learning · Computer Science 2020-01-01 Aviral Kumar , Xue Bin Peng , Sergey Levine

We study a model of a corporation which has the possibility to choose various production/business policies with different expected profits and risks. In the model there are restrictions on the dividend distribution rates as well as…

Probability · Mathematics 2008-12-10 Tahir Choulli , Michael Taksar , Xun Yu Zhou

Autonomous agents that act with each other on behalf of humans are becoming more common in many social domains, such as customer service, transportation, and health care. In such social situations greedy strategies can reduce the positive…

Multiagent Systems · Computer Science 2022-12-02 Jory Schossau , Bamshad Shirmohammadi , Arend Hintze

We consider the design of experiments to evaluate treatments that are administered by self-interested agents, each seeking to achieve the highest evaluation and win the experiment. For example, in an advertising experiment, a company wishes…

Methodology · Statistics 2015-09-18 Panos Toulis , David C. Parkes , Elery Pfeffer , James Zou

Most demand management approaches with non-mandatory policies assume full users' cooperation, which may not be the case given users' beliefs, needs and preferences. In this paper we propose a mechanism for demand management including…

Computer Science and Game Theory · Computer Science 2017-10-30 Mateo Alejandro Cortés Guzmán , Eduardo Mojica-Nava

Many incentive design problems must contend with information asymmetries due to non-observation of efficiency (adverse selection) or non-observation of effort (moral hazard). And although a growing body of literature considers incentive…

Optimization and Control · Mathematics 2026-05-04 Jaewon Jeong , Pan-Yang Su , S. Shankar Sastry , Anil Aswani

Institutions and investors face the constant challenge of making accurate decisions and predictions regarding how best they should distribute their endowments. The problem of achieving an optimal outcome at minimal cost has been extensively…

Multiagent Systems · Computer Science 2021-02-09 Theodor Cimpeanu , Cedric Perret , The Anh Han

When deploying artificial agents in real-world environments where they interact with humans, it is crucial that their behavior is aligned with the values, social norms or other requirements of that environment. However, many environments…

Machine Learning · Computer Science 2023-05-05 Mattijs Baert , Pietro Mazzaglia , Sam Leroux , Pieter Simoens
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