Equilibrium and optimal one-shot delegated search

Hassin, Refael

doi:10.1080/24725854.2019.1663085

Cited by 2 publications

(2 citation statements)

References 22 publications

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“…Also, several ‘emergent properties’ of the KPR game, such as the utilization fraction or the occupation density in the steady or stable states, and phase transition behavior, have been numerically studied in Tamir ( 2018 ). A search problem often arises as a time-limited business opportunity by business firms, and is studied like a one-shot delegated search in Hassin ( 2021 ). Authors here had discussed and investigated the searchers' incentives following different strategies, including KPR, can maximize search success.…”

Section: Summary and Discussionmentioning

confidence: 99%

Stochastic Learning in Kolkata Paise Restaurant Problem: Classical and Quantum Strategies

Chakrabarti

Rajak

Sinha³

2022

Front. Artif. Intell.

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We review the results for stochastic learning strategies, both classical (one-shot and iterative) and quantum (one-shot only), for optimizing the available many-choice resources among a large number of competing agents, developed over the last decade in the context of the Kolkata Paise Restaurant (KPR) Problem. Apart from few rigorous and approximate analytical results, both for classical and quantum strategies, most of the interesting results on the phase transition behavior (obtained so far for the classical model) uses classical Monte Carlo simulations. All these including the applications to computer science [job or resource allotments in Internet-of-Things (IoT)], transport engineering (online vehicle hire problems), operation research (optimizing efforts for delegated search problem, efficient solution of Traveling Salesman problem) will be discussed.

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Section: Summary and Discussionmentioning

confidence: 99%

Stochastic Learning in Kolkata Paise Restaurant Problem: Classical and Quantum Strategies

Chakrabarti

Rajak

Sinha³

2022

Front. Artif. Intell.

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“…Also, several 'emergent properties' of the KPR game, such as the utilization fraction or the occupation density in the steady or stable states, phase transition behavior, etc., have been numerically studied in [48]. A search problem often arises as a time-limited business opportunity by business firms, and is studied like an one-shot delegated search in [49]. Authors here had discussed and investigated the searchers' incentives following different strategies, including KPR, that can maximize the search success.…”

Section: Summary and Discussionmentioning

confidence: 99%

Stochastic Learning in Kolkata Paise Restaurant Problem: Classical \& Quantum Strategies

Chakrabarti¹,

Rajak²,

Sinha³

2022

Preprint

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We will review the results for stochastic learning strategies, both classical (one-shot and iterative) and quantum (one-shot only), for optimizing the available many-choice resources among a large number of competing agents, developed over the last decade in the context of the Kolkata Paise Restaurant Problem. Apart from a few rigorous and approximate analytical results, both for classical and quantum strategies, most of the interesting results on the phase transition behavior (obtained so far for the classical model) using classical Monte Carlo simulations. All these, including the applications to computer science (job or resource allotments in Internet-of-Things), transport engineering (on-line vehicle hire problems), operation research (optimizing efforts for delegated search problem, efficient solution of Travelling Salesman problem), etc will be discussed.

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Equilibrium and optimal one-shot delegated search

Cited by 2 publications

References 22 publications

Stochastic Learning in Kolkata Paise Restaurant Problem: Classical and Quantum Strategies

Stochastic Learning in Kolkata Paise Restaurant Problem: Classical and Quantum Strategies

Stochastic Learning in Kolkata Paise Restaurant Problem: Classical \& Quantum Strategies

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