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Shapley value is a popular approach for measuring the influence of individual features. While Shapley feature attribution is built upon desiderata from game theory, some of its constraints may be less natural in certain machine learning…

Machine Learning · Computer Science 2022-09-28 Yongchan Kwon , James Zou

With machine learning models being increasingly used to aid decision making even in high-stakes domains, there has been a growing interest in developing interpretable models. Although many supposedly interpretable models have been proposed,…

Artificial Intelligence · Computer Science 2021-08-17 Forough Poursabzi-Sangdeh , Daniel G. Goldstein , Jake M. Hofman , Jennifer Wortman Vaughan , Hanna Wallach

We compare two approaches for modelling imperfect information in infinite games by using finite-state automata. The first, more standard approach views information as the result of an observation process driven by a sequential Mealy…

Computer Science and Game Theory · Computer Science 2020-01-31 Dietmar Berwanger , Laurent Doyen

Software Transactional Memory (STM) algorithms provide programmers with a synchronisation mechanism for concurrent access to shared variables. Basically, programmers can specify transactions (reading from and writing to shared state) which…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-07-02 Heike Wehrheim

We conceptualize explainability in terms of logic and formula size, giving a number of related definitions of explainability in a very general setting. Our main interest is the so-called special explanation problem which aims to explain the…

Artificial Intelligence · Computer Science 2022-10-26 Reijo Jaakkola , Tomi Janhunen , Antti Kuusisto , Masood Feyzbakhsh Rankooh , Miikka Vilander

The growing use of machine learning models in consequential settings has highlighted an important and seemingly irreconcilable tension between transparency and vulnerability to gaming. While this has sparked sizable debate in legal…

Machine Learning · Computer Science 2022-02-24 Tom Yan , Chicheng Zhang

We study the computational complexity of an important property of simple, regular and weighted games, which is decisiveness. We show that this concept can naturally be represented in the context of hypergraph theory, and that decisiveness…

Computer Science and Game Theory · Computer Science 2013-07-10 Andreas Polyméris , Fabián Riquelme

This mini-review presents extensions of the voter model that incorporate various plausible features of real decision-making processes by individuals. Although these generalizations are not calibrated by empirical data, the resulting…

Physics and Society · Physics 2019-07-31 S. Redner

Researchers in explainable artificial intelligence have developed numerous methods for helping users understand the predictions of complex supervised learning models. By contrast, explaining the $\textit{uncertainty}$ of model outputs has…

Machine Learning · Statistics 2023-11-01 David S. Watson , Joshua O'Hara , Niek Tax , Richard Mudd , Ido Guy

We introduce a way to parameterize automata and games on finite graphs with natural numbers. The parameters are accessed essentially by allowing counting down from the parameter value to 0 and branching depending on whether 0 has been…

Computer Science and Game Theory · Computer Science 2018-09-11 Arno Pauly

We present a large deviation property for the pattern statistics representing the number of occurrences of a symbol in words of given length generated at random according to a rational stochastic model. The result is obtained assuming that…

Probability · Mathematics 2023-06-14 Massimiliano Goldwurm , Marco Vignati

Purpose: We propose a model to present a possible mechanism for obtaining sizeable behavioural structures by simulating an agent based on the evolutionary public good game with available social learning. Methods: The model considered a…

Computer Science and Game Theory · Computer Science 2019-10-29 Chulwook Park

We consider the model checking problem for probabilistic pushdown automata (pPDA) and properties expressible in various probabilistic logics. We start with properties that can be formulated as instances of a generalized random walk problem.…

Logic in Computer Science · Computer Science 2017-01-11 Javier Esparza , Antonin Kucera , Richard Mayr

A new simple model of financial market is proposed, based on the sequential and inter-temporal nature of trader-trader interaction, and on a new simple trading strategy space. In this pattern-based speculation model, the traders open and…

Physics and Society · Physics 2007-05-23 Damien Challet

We study the role of imitation within the Minority Game model of market. The players can exchange information locally, which leads to formation of groups which act as if they were single players. Coherent spatial areas of rich and poor…

Statistical Mechanics · Physics 2009-10-31 Frantisek Slanina

Value methods for solving stochastic games with partial observability model the uncertainty about states of the game as a probability distribution over possible states. The dimension of this belief space is the number of states. For many…

Computer Science and Game Theory · Computer Science 2019-03-14 Karel Horák , Branislav Bošanský , Christopher Kiekintveld , Charles Kamhoua

This article deals with plausible reasoning from incomplete knowledge about large-scale spatial properties. The availableinformation, consisting of a set of pointwise observations,is extrapolated to neighbour points. We make use of belief…

Artificial Intelligence · Computer Science 2013-01-14 Jerome Lang , Philippe Muller

The use of game theoretic methods for control in multiagent systems has been an important topic in recent research. Valid utility games in particular have been used to model real-world problems; such games have the convenient property that…

Computer Science and Game Theory · Computer Science 2022-09-16 David Grimsman , Philip N. Brown , Jason R. Marden

A brief review is given of the minority game, an idealized model stimulated by a market of speculative agents, and its complex many-body behaviour. Particular consideration is given to analytic results for the model rather than discussions…

Disordered Systems and Neural Networks · Physics 2009-11-11 David Sherrington

Inspired by the theory of desirable gambles that is used to model uncertainty in the field of imprecise probabilities, I present a theory of desirable things. Its aim is to model a subject's beliefs about which things are desirable. What…

Artificial Intelligence · Computer Science 2023-05-12 Jasper De Bock