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Efficient exploration is an unsolved problem in Reinforcement Learning which is usually addressed by reactively rewarding the agent for fortuitously encountering novel situations. This paper introduces an efficient active exploration…

Machine Learning · Computer Science 2019-06-17 Pranav Shyam , Wojciech Jaśkowski , Faustino Gomez

Inspired by e-participation systems, in this paper we propose a new model to represent human debates and methods to obtain collective conclusions from them. This model overcomes drawbacks of existing approaches by allowing users to…

Artificial Intelligence · Computer Science 2020-07-15 Jordi Ganzer , Natalia Criado , Maite Lopez-Sanchez , Simon Parsons , Juan A. Rodriguez-Aguilar

Research in data warehousing and OLAP has produced important technologies for the design, management and use of information systems for decision support. With the development of Internet, the availability of various types of data has…

We introduce an optimisation method for variational quantum algorithms and experimentally demonstrate a 100-fold improvement in efficiency compared to naive implementations. The effectiveness of our approach is shown by obtaining…

In order to truly understand how social media might shape online discourses or contribute to societal polarization, we need refined models of platform choice, that is: models that help us understand why users prefer one social media…

Adaptation and Self-Organizing Systems · Physics 2024-11-08 Sven Banisch , Dennis Jacob , Tom Willaert , Eckehard Olbrich

Real world experiments are expensive, and thus it is important to reach a target in minimum number of experiments. Experimental processes often involve control variables that changes over time. Such problems can be formulated as a…

In contrast to typical laboratory experiments, the everyday use of online educational resources by large populations and the prevalence of software infrastructure for A/B testing leads us to consider how platforms can embed in vivo…

Human-Computer Interaction · Computer Science 2015-02-17 Joseph Jay Williams , Korinn Ostrow , Xiaolu Xiong , Elena Glassman , Juho Kim , Samuel G. Maldonado , Na Li , Justin Reich , Neil Hefferman

This paper develops methods of distributed Bayesian hypothesis tests for fault detection and diagnosis that are based on belief propagation and optimization in graphical models. The main challenges in developing distributed statistical…

Systems and Control · Computer Science 2015-01-20 Kwang-Ki K. Kim

Turbulent dynamical systems are characterized by nonlinear interactions and stochastic effects that generate coupled statistical quantities, such as non-zero higher-order moments, which are difficult to capture from data with accuracy. We…

Machine Learning · Computer Science 2026-05-12 Xingjian Xu , Di Qi , Chunmei Wang

This paper describes valuation-based systems for representing and solving discrete optimization problems. In valuation-based systems, we represent information in an optimization problem using variables, sample spaces of variables, a set of…

Artificial Intelligence · Computer Science 2013-04-05 Prakash P. Shenoy , Glenn Shafer

We study several models of growth driven by innovation and imitation by a continuum of firms, focusing on the interaction between the two. We first investigate a model on a technology ladder where innovation and imitation combine to…

Theoretical Economics · Economics 2020-08-27 Jess Benhabib , Éric Brunet , Mildred Hager

XP is a light-weight methodology suited particularly for small-sized teams that develop software which has only vague or rapidly changing requirements. The discipline of systems engineering knows it as approach of incremental system change…

Software Engineering · Computer Science 2014-09-25 Carsten Jacobi , Bernhard Rumpe

Optimal design facilitates intelligent data collection. In this paper, we introduce a fully Bayesian design approach for spatial processes with complex covariance structures, like those typically exhibited in natural ecosystems. Coordinate…

There is significant interest in learning and optimizing a complex system composed of multiple sub-components, where these components may be agents or autonomous sensors. Among the rich literature on this topic, agent-based and…

Machine Learning · Computer Science 2021-07-08 Kai Wang , Bryan Wilder , Sze-chuan Suen , Bistra Dilkina , Milind Tambe

We present the public release of EXP, a basis function expansion C++ library and Python package for running N-body galactic simulations and dynamical discovery. EXP grew out of the need for methodology that seamlessly connects theoretical…

Astrophysics of Galaxies · Physics 2025-05-13 Michael S. Petersen , Martin D. Weinberg

Joint state and parameter estimation is a core problem for dynamic Bayesian networks. Although modern probabilistic inference toolkits make it relatively easy to specify large and practically relevant probabilistic models, the silver…

Artificial Intelligence · Computer Science 2016-03-31 Yusuf Bugra Erol , Yi Wu , Lei Li , Stuart Russell

Computational multiscale methods for analyzing and deriving constitutive responses have been used as a tool in engineering problems because of their ability to combine information at different length scales. However, their application in a…

Machine Learning · Statistics 2021-08-03 Jan Niklas Fuhg , Christoph Boehm , Nikolaos Bouklas , Amelie Fau , Peter Wriggers , Michele Marino

This paper describes a series of model-checking experiments to verify optimistic replication algorithms based on Operational Transformation (OT) approach used for supporting collaborative edition. We formally define, using tool UPPAAL, the…

Logic in Computer Science · Computer Science 2009-04-20 Hanifa Boucheneb , Abdessamad Imine

This essay advocates the view that any problem that has a meaningful empirical content, can be formulated in constructive, more definitely, finite terms. We consider combinatorial models of dynamical systems and approaches to statistical…

Quantum Physics · Physics 2015-07-21 Vladimir V. Kornyak

Simulation offers a simple and flexible way to estimate the power of a clinical trial when analytic formulae are not available. The computational burden of using simulation has, however, restricted its application to only the simplest of…

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