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Piece of Pie Search: Confidently Exploiting Heuristics

Published: 18 May 2016 Publication History

Abstract

Search is not a direct path to a solution. While searching for a solution to a problem, heuristics consult us to avoid paths with dead ends, but they are not infallible. Many popular search methodologies "disobey" them during critical points of the search. In this work, we found an efficient stochastic methods framework that smoothly combines randomness with normal heuristics. We consider a factor of disobedience to the heuristics and we fine-tune it each time, according to our estimation of heuristic-reliability. We prove mathematically that while the disobedience factor falls, the stochastic methods approximate deterministic methods. Our algebraic evidence is supported by empirical evaluations on real life problems, such as course scheduling and frequency assignment. In this context, we exploit our proposed heuristic-reliability semantics in order to produce a piece of pie search (PoPS) method that can outperform other known constructive search processes in hard optimization problems.

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  1. Piece of Pie Search: Confidently Exploiting Heuristics

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    SETN '16: Proceedings of the 9th Hellenic Conference on Artificial Intelligence
    May 2016
    249 pages
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 18 May 2016

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    Author Tags

    1. CSP
    2. confidence
    3. constructive search
    4. discrepancy
    5. randomness
    6. stochastic methods

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