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Related papers: Parallel Search for Information

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A researcher observes a finite sequence of choices made by multiple agents in a binary-state environment. Agents maximize expected utilities that depend on their chosen alternative and the unknown underlying state. Agents learn about the…

Theoretical Economics · Economics 2021-05-11 Rahul Deb , Ludovic Renou

The problem of content search through comparisons has recently received considerable attention. In short, a user searching for a target object navigates through a database in the following manner: the user is asked to select the object most…

Machine Learning · Computer Science 2014-02-11 Amin Karbasi , Stratis Ioannidis , Laurent Massoulie

Evolving Neural Networks (NNs) has recently seen an increasing interest as an alternative path that might be more successful. It has many advantages compared to other approaches, such as learning the architecture of the NNs. However, the…

Neural and Evolutionary Computing · Computer Science 2022-03-15 Abdullah Khalili , Abdelhamid Bouchachia

When foraging for information, users face a tradeoff between the accuracy and value of the acquired information and the time spent collecting it, a problem which also surfaces when seeking answers to a question posed to a large community.…

Computers and Society · Computer Science 2010-08-31 Christina Aperjis , Bernardo A. Huberman , Fang Wu

Sellers in online markets face the challenge of determining the right time to sell in view of uncertain future offers. Classical stopping theory assumes that sellers have full knowledge of the value distributions, and leverage this…

Theoretical Economics · Economics 2022-06-30 Pieter Kleer , Johan van Leeuwaarden

Given a sequence of independent random variables with a common continuous distribution, we consider the online decision problem where one seeks to minimize the expected value of the time that is needed to complete the selection of a…

Probability · Mathematics 2016-09-05 Alessandro Arlotto , Elchanan Mossel , J. Michael Steele

Active learning allows machine learning models to be trained using fewer labels while retaining similar performance to traditional supervised learning. An active learner selects the most informative data points, requests their labels, and…

Machine Learning · Computer Science 2023-11-22 Zac Pullar-Strecker , Katharina Dost , Eibe Frank , Jörg Wicker

Two mobile agents, starting from different nodes of a network at possibly different times, have to meet at the same node. This problem is known as $\mathit{rendezvous}$. Agents move in synchronous rounds. Each agent has a distinct integer…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-08-12 Avery Miller , Andrzej Pelc

I consider the monopolistic pricing of informational good. A buyer's willingness to pay for information is from inferring the unknown payoffs of actions in decision making. A monopolistic seller and the buyer each observes a private signal…

Theoretical Economics · Economics 2018-10-18 Weijie Zhong

We carry out a comparative study on the problem for a walker searching on several typical complex networks. The search efficiency is evaluated for various strategies. Having no knowledge of the global properties of the underlying networks…

Disordered Systems and Neural Networks · Physics 2009-11-10 Shi-Jie Yang

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

Many academic disciplines - including information systems, computer science, and operations management - face scheduling problems as important decision making tasks. Since many scheduling problems are NP-hard in the strong sense, there is a…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-05-26 Gerhard Rauchecker , Guido Schryen

The problem of searchability in decentralized complex networks is of great importance in computer science, economy and sociology. We present a formalism that is able to cope simultaneously with the problem of search and the congestion…

Disordered Systems and Neural Networks · Physics 2009-11-07 R. Guimera , A. Arenas , A. Diaz-Guilera , F. Vega-Redondo , A. Cabrales

We consider online variations of the Pandora's box problem (Weitzman. 1979), a standard model for understanding issues related to the cost of acquiring information for decision-making. Our problem generalizes both the classic Pandora's box…

Data Structures and Algorithms · Computer Science 2019-01-31 Hossein Esfandiari , MohammadTaghi Hajiaghayi , Brendan Lucier , Michael Mitzenmacher

In business, politics and life, folk wisdom encourages people to aim for above-average results, but to not let the perfect be the enemy of the good. Here, we mathematically formalize and extend this folk wisdom. We model a time-limited…

Physics and Society · Physics 2026-02-11 Ekaterina Landgren , Ryan E. Langendorf , Matthew G. Burgess

A dominant cost for query evaluation in modern massively distributed systems is the number of communication rounds. For this reason, there is a growing interest in single-round multiway join algorithms where data is first reshuffled over…

Databases · Computer Science 2015-01-06 Tom J. Ameloot , Gaetano Geck , Bas Ketsman , Frank Neven , Thomas Schwentick

Information-theoretic bounded rationality describes utility-optimizing decision-makers whose limited information-processing capabilities are formalized by information constraints. One of the consequences of bounded rationality is that…

Machine Learning · Computer Science 2020-06-30 Heinke Hihn , Sebastian Gottwald , Daniel A. Braun

We introduce the profligacy of a search process as a competition between its expected cost and the probability of finding the target. The arbiter of the competition is a parameter $\lambda$ that represents how much a searcher invests into…

Statistical Mechanics · Physics 2024-10-11 John C. Sunil , Richard A. Blythe , Martin R. Evans , Satya N. Majumdar

Perfectly rational decision-makers maximize expected utility, but crucially ignore the resource costs incurred when determining optimal actions. Here we employ an axiomatic framework for bounded rational decision-making based on a…

Artificial Intelligence · Computer Science 2011-07-29 Pedro A. Ortega , Daniel A. Braun

We study the Pareto frontier (optimal trade-off) between utility and separation, a fairness criterion requiring predictive independence from sensitive attributes conditional on the true outcome. Through an information-theoretic lens, we…

Machine Learning · Computer Science 2026-02-06 Shizhou Xu
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