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Klavik et al. [arXiv:1207.6960] recently introduced a generalization of recognition called the bounded representation problem which we study for the classes of interval and proper interval graphs. The input gives a graph G and in addition…

Discrete Mathematics · Computer Science 2013-09-06 Martin Balko , Pavel Klavík , Yota Otachi

Fairness is a major concern in contemporary decision problems. In these situations, the objective is to maximize fairness while preserving the efficacy of the underlying decision-making problem. This paper examines repeated decisions on…

Optimization and Control · Mathematics 2022-12-21 Andrea Lodi , Sriram Sankaranarayanan , Guanyi Wang

The Equation Problem in finitely presented groups asks if there exists an algorithm which determines in finite amount of time whether any given equation system has a solution or not. We show that the Equation Problem in central extensions…

Group Theory · Mathematics 2013-07-24 Hao Liang

History-deterministic automata are those in which nondeterministic choices can be correctly resolved stepwise: there is a strategy to select a continuation of a run given the next input letter so that if the overall input word admits some…

Formal Languages and Automata Theory · Computer Science 2026-04-01 Soumyajit Paul , David Purser , Sven Schewe , Qiyi Tang , Patrick Totzke , Di-De Yen

Autonomous agents are seen as a prominent technology to be applied in industrial scenarios. Classical automation solutions are struggling with challenges related to high dynamism, prompt actuation, heterogeneous entities, including humans,…

We give full account of our recent report in [E.A. Galapon, R. Caballar, R. Bahague {\it Phys. Rev. Let.} {\bf 93} 180406 (2004)] where it is shown that formulating the free quantum time of arrival problem in a segment of the real line…

Quantum Physics · Physics 2009-11-11 Eric A. Galapon , Roland F. Caballar , Ricardo Bahague

In this paper the approach to solving several combinatorial optimization problems using the local search and the genetic algorithm techniques is proposed. Initially this approach was developed in purpose to overcome some difficulties…

Neural and Evolutionary Computing · Computer Science 2010-04-30 Anton Bondarenko

Advances in computing power and data availability have led to growing sophistication in mechanistic mathematical models of social dynamics. Increasingly these models are used to inform real-world policy decision-making, often with…

In economic theory, an agent chooses from available alternatives -- modeled as a set. In decisions in the field or in the lab, however, agents do not have access to the set of alternatives at once. Instead, alternatives are represented by…

Computer Science and Game Theory · Computer Science 2021-11-09 Paulo Oliva , Philipp Zahn

In this work the properties of minority games containing agents which try to winning all the time are studied by means of computational simulations. We have considered several ways of introducing above the rules clever players using…

Disordered Systems and Neural Networks · Physics 2007-05-23 J. R. L. de Almeida , J. Menche

Metaheuristics are universal optimization algorithms which should be used for solving difficult problems, unsolvable by classic approaches. In this paper we aim at constructing novel socio-cognitive metaheuristic based on castes, and apply…

We consider infinite horizon dynamic programming problems, where the control at each stage consists of several distinct decisions, each one made by one of several agents. In an earlier work we introduced a policy iteration algorithm, where…

Optimization and Control · Mathematics 2020-05-05 Dimitri Bertsekas

We revisit classic algorithmic search and optimization problems from the perspective of competition. Rather than a single optimizer minimizing expected cost, we consider a zero-sum game in which an optimization problem is presented to two…

Computer Science and Game Theory · Computer Science 2011-01-17 Nicole Immorlica , Adam Tauman Kalai , Brendan Lucier , Ankur Moitra , Andrew Postlewaite , Moshe Tennenholtz

An intelligent agent may in general pursue multiple procedural goals simultaneously, which may lead to arise some conflicts (incompatibilities) among them. In this paper, we focus on the incompatibilities that emerge due to resources…

Artificial Intelligence · Computer Science 2020-09-15 Mariela Morveli-Espinoza , Ayslan Possebom , Cesar Augusto Tacla

We consider the discrete assignment problem in which agents express ordinal preferences over objects and these objects are allocated to the agents in a fair manner. We use the stochastic dominance relation between fractional or randomized…

Computer Science and Game Theory · Computer Science 2015-06-18 Haris Aziz , Serge Gaspers , Simon Mackenzie , Toby Walsh

We apply classical algorithms for approximately solving constraint satisfaction problems to find bounds on extremal eigenvalues of local Hamiltonians. We consider spin Hamiltonians for which we have an upper bound on the number of terms in…

Quantum Physics · Physics 2017-04-26 Aram W. Harrow , Ashley Montanaro

Experimental mathematics is an experimental approach to mathematics in which programming and symbolic computation are used to investigate mathematical objects, identify properties and patterns, discover facts and formulas and even…

Combinatorics · Mathematics 2020-05-19 Yukun Yao

We give formal content to some concepts, naturally stemming from consistent history approach (CHA), which are not formalized in the standard formulation of the theory. The outcoming (extended) conceptual basis is used to perform a formal,…

Quantum Physics · Physics 2015-06-26 Giuseppe Nistico'

Comparisons of different treatments or production processes are the goals of a significant fraction of applied research. Unsurprisingly, two-sample problems play a main role in Statistics through natural questions such as `Is the the new…

Methodology · Statistics 2017-09-05 P. C. Álvarez-Esteban , E. del Barrio , J. A. Cuesta-Albertos , C. Matrán

We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained during execution of one task has value for the execution of…

Machine Learning · Computer Science 2012-09-06 Christos Dimitrakakis
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