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Negotiation is a very common interaction between automated agents. Many common negotiation protocols work with cardinal utilities, even though ordinal preferences, which only rank the outcomes, are easier to elicit from humans. In this work…

Computer Science and Game Theory · Computer Science 2023-12-18 Sefi Erlich , Noam Hazon , Sarit Kraus

Selection of input features such as relevant pieces of text has become a common technique of highlighting how complex neural predictors operate. The selection can be optimized post-hoc for trained models or incorporated directly into the…

Machine Learning · Computer Science 2019-10-29 Shiyu Chang , Yang Zhang , Mo Yu , Tommi S. Jaakkola

We propose models for lobbying in a probabilistic environment, in which an actor (called "The Lobby") seeks to influence voters' preferences of voting for or against multiple issues when the voters' preferences are represented in terms of…

Computational Complexity · Computer Science 2011-03-01 Daniel Binkele-Raible , Gábor Erdélyi , Henning Fernau , Judy Goldsmith , Nicholas Mattei , Jörg Rothe

Computing the Nash equilibrium (NE) for N-player non-zerosum stochastic games is a formidable challenge. Currently, algorithmic methods in stochastic game theory are unable to compute NE for stochastic games (SGs) for settings in all but…

Optimization and Control · Mathematics 2021-03-25 David Mguni

Argumentation is a non-monotonic process. This reflects the fact that argumentation involves uncertain information, and so new information can cause a change in the conclusions drawn. However, the base logic does not need to be…

Artificial Intelligence · Computer Science 2018-09-05 Anthony Hunter

This paper presents an approach that brings together game theory with grammatical inference and discrete abstractions in order to synthesize control strategies for hybrid dynamical systems performing tasks in partially unknown but…

Robotics · Computer Science 2012-10-08 Jie Fu , Herbert G. Tanner , Jeffrey Heinz , Jane Chandlee , Konstantinos Karydis , Cesar Koirala

The best-response dynamics is an example of an evolutionary game where players update their strategy in order to maximize their payoff. The main objective of this paper is to study a stochastic spatial version of this game based on the…

Probability · Mathematics 2014-07-28 Stephen Evilsizor , Nicolas Lanchier

Game theory has been developed by scientists as a theory of strategic interaction among players who are supposed to be perfectly rational. These strategic interactions might have been presented in an auction, a business negotiation, a chess…

Computer Science and Game Theory · Computer Science 2020-04-07 Medet Kanmaz , Elif Surer

Strategic interactions between competitive entities are generally considered from the perspective of complete revelation of benefits achieved from those interactions, in the form of public payoff functions and/or beliefs, in the announced…

Computer Science and Game Theory · Computer Science 2020-02-12 Aditya Ahuja

We consider turn-based stochastic two-player games with a combination of a parity condition that must hold surely, that is in all possible outcomes, and of a parity condition that must hold almost-surely, that is with probability 1. The…

Computer Science and Game Theory · Computer Science 2026-01-08 Laurent Doyen , Shibashis Guha

We consider an extension of the classical Total Store Order (TSO) semantics by expanding it to turn-based 2-player safety games. During her turn, a player can select any of the communicating processes and perform its next transition. We…

Computer Science and Game Theory · Computer Science 2023-10-03 Stephan Spengler , Sanchari Sil

Strategy iteration is a technique frequently used for two-player games in order to determine the winner or compute payoffs, but to the best of our knowledge no general framework for strategy iteration has been considered. Inspired by…

Logic in Computer Science · Computer Science 2022-12-14 Paolo Baldan , Richard Eggert , Barbara König , Tommaso Padoan

To make AI systems broadly useful for challenging real-world tasks, we need them to learn complex human goals and preferences. One approach to specifying complex goals asks humans to judge during training which agent behaviors are safe and…

Machine Learning · Statistics 2018-10-23 Geoffrey Irving , Paul Christiano , Dario Amodei

We define and investigate a property of mechanisms that we call "strategic simplicity," and that is meant to capture the idea that, in strategically simple mechanisms, strategic choices require limited strategic sophistication. We define a…

Theoretical Economics · Economics 2018-12-04 Tilman Borgers , Jiangtao Li

The relationship between topology and dynamics of complex systems has motivated continuing interest from the scientific community. In the present work, we address this interesting topic from the perspective of simple games, involving two…

Social and Information Networks · Computer Science 2024-06-25 Alexandre Benatti , Luciano da F. Costa

We study learning in complete-information games, allowing the players' models of their environment to be misspecified. We introduce Berk--Nash rationalizability: the largest self-justified set of actions -- meaning each action in the set is…

Theoretical Economics · Economics 2025-10-28 Ignacio Esponda , Demian Pouzo

We introduce the notion of logical A-games for a fairly general class of algebras A of real truth-values. This concept generalizes the Boolean games of Harrenstein et al. as well as the recently defined Lukasiewicz games of Marchioni and…

Logic · Mathematics 2016-01-05 Libor Běhounek , Petr Cintula , Chris Fermüller , Tomáš Kroupa

We provide a compositional coalgebraic semantics for strategic games. In our framework, like in the semantics of functional programming languages, coalgebras represent the observable behaviour of systems derived from the behaviour of the…

Computer Science and Game Theory · Computer Science 2017-12-25 Achim Blumensath , Viktor Winschel

Games with incomplete preferences are an important model for studying rational decision-making in scenarios where players face incomplete information about their preferences and must contend with incomparable outcomes. We study the problem…

Computer Science and Game Theory · Computer Science 2024-08-13 Abhishek N. Kulkarni , Jie Fu , Ufuk Topcu

In this paper we describe an approach to resolve strategic games in which players can assume different types along the game. Our goal is to infer which type the opponent is adopting at each moment so that we can increase the player's odds.…

Computer Science and Game Theory · Computer Science 2014-04-02 Mario Benevides , Isaque Lima , Rafael Nader , Pedro Rougemont
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