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In systems modelling, a 'system' typically comprises located resources relative to which processes execute. One important use of logic in informatics is in modelling such systems for the purpose of reasoning (perhaps automated) about their…

Logic in Computer Science · Computer Science 2024-12-18 Alexander V. Gheorghiu , Tao Gu , David J. Pym

It has been proposed that human physical reasoning consists largely of running "physics engines in the head" in which the future trajectory of the physical system under consideration is computed precisely using accurate scientific theories.…

Artificial Intelligence · Computer Science 2015-06-17 Ernest Davis , Gary Marcus

Using coalgebraic methods, we extend Conway's theory of games to possibly non-terminating, i.e. non-wellfounded games (hypergames). We take the view that a play which goes on forever is a draw, and hence rather than focussing on winning…

Logic in Computer Science · Computer Science 2015-07-01 Furio Honsell , Marina Lenisa

There are many examples of human decision making which cannot be modeled by classical probabilistic and logic models, on which the current AI systems are based. Hence the need for a modeling framework which can enable intelligent systems to…

Artificial Intelligence · Computer Science 2018-08-15 Sagar Uprety , Dawei Song

Standard economic theory assumes that agents in markets behave rationally. However, the observation of extremely large fluctuations in the price of financial assets that are not correlated to changes in their fundamental value, as well as…

Physics and Society · Physics 2015-06-26 Sitabhra Sinha

Common knowledge is crucial for safe group coordination. In its absence, humans must rely on shared knowledge, which is inherently limited in depth and therefore prone to coordination failures, because any finite-order knowledge attribution…

Multiagent Systems · Computer Science 2025-11-12 Thomas Bolander , Robin Engelhardt , Thomas S. Nicolet

Coordination is a desirable feature in many multi-agent systems such as robotic and socioeconomic networks. We consider a task allocation problem as a binary networked coordination game over an undirected regular graph. Each agent in the…

Systems and Control · Electrical Eng. & Systems 2023-10-02 Yifei Zhang , Marcos M. Vasconcelos

Human decision behaviour is quite diverse. In many games humans on average do not achieve maximal payoff and the behaviour of individual players remains inhomogeneous even after playing many rounds. For instance, in repeated prisoner…

Physics and Society · Physics 2015-11-11 Martin Spanknebel , Klaus Pawelzik

With recent advances in natural language processing, rationalization becomes an essential self-explaining diagram to disentangle the black box by selecting a subset of input texts to account for the major variation in prediction. Yet,…

Machine Learning · Computer Science 2023-09-12 Wenbo Zhang , Tong Wu , Yunlong Wang , Yong Cai , Hengrui Cai

We consider a computing system where a master processor assigns tasks for execution to worker processors through the Internet. We model the workers decision of whether to comply (compute the task) or not (return a bogus result to save the…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-08-25 Antonio Fernández Anta , Chryssis Georgiou , Miguel A. Mosteiro , Daniel Pareja

Inductions and game semantics are two useful extensions to traditional logic programming. To be specific, inductions can capture a wider class of provable formulas in logic programming. Adopting game semantics can make logic programming…

Logic in Computer Science · Computer Science 2015-08-11 Keehang Kwon

We study a simple example of a sequential game illustrating problems connected with making rational decisions that are universal for social sciences. The set of chooser's optimal decisions that manifest his preferences in case of a constant…

Physics and Society · Physics 2007-05-23 Edward W. Piotrowski , Marcin Makowski

What is reasoning? This question has driven centuries of philosophical inquiry, from Aristotle's syllogisms to modern computational complexity theory. In the age of large language models achieving superhuman performance on benchmarks like…

Machine Learning · Computer Science 2025-11-18 Zixi Li

The term rational has become synonymous with maximizing expected payoff in the definition of the best response in Nash setting. In this work, we consider stochastic games in which players engage only once, or at most a limited number of…

Computer Science and Game Theory · Computer Science 2020-02-21 Ali Yekkehkhany , Timothy Murray , Rakesh Nagi

Graph games of infinite length are a natural model for open reactive processes: one player represents the controller, trying to ensure a given specification, and the other represents a hostile environment. The evolution of the system…

Computer Science and Game Theory · Computer Science 2010-06-09 Julien Cristau , Claire David , Florian Horn

Assuming humans are (approximately) rational enables robots to infer reward functions by observing human behavior. But people exhibit a wide array of irrationalities, and our goal with this work is to better understand the effect they can…

Machine Learning · Computer Science 2021-11-16 Lawrence Chan , Andrew Critch , Anca Dragan

We attempt to make superdeterminism more intuitive, notably by simulating a deterministic model system, a billiard game. In this system an initial 'bang' correlates all events, just as in the superdeterministic universe. We introduce the…

Quantum Physics · Physics 2023-01-04 Vitaly Nikolaev , Louis Vervoort

Subjective expected utility theory assumes that decision-makers possess unlimited computational resources to reason about their choices; however, virtually all decisions in everyday life are made under resource constraints - i.e.…

Machine Learning · Statistics 2016-10-07 Pedro A. Ortega , Alan A. Stocker

We study an evolutionary game of chance in which the probabilities for different outcomes (e.g., heads or tails) depend on the amount wagered on those outcomes. The game is perhaps the simplest possible probabilistic game in which…

Physics and Society · Physics 2007-08-29 Dmitriy Cherkashin , J. Doyne Farmer , Seth Lloyd

While game theory is widely used to model strategic interactions, a natural question is where do the game representations come from? One answer is to learn the representations from data. If one wants to learn both the payoffs and the…

Computer Science and Game Theory · Computer Science 2012-03-19 Xi Alice Gao , Avi Pfeffer
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