PALO: a probabilistic hill-climbing algorithm
نویسندگان
چکیده
منابع مشابه
PALO: A Probabilistic Hill-Climbing Algorithm
Many learning systems search through a space of possible performance elements, seeking an element whose expected utility, over the distribution of problems, is high. As the task of nding the globally optimal element is often intractable, many practical learning systems instead hill-climb to a local optimum. Unfortunately, even this is problematic as the learner typically does not know the under...
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Many learning tasks involve searching through a discrete space of performance elements, seeking an element whose future utility is expected to be high. As the task of nding the global optimum is often intractable, many practical learning systems use simple forms of hill-climbing to nd a locally optimal element. However, hill-climbing can be complicated by the fact that the utility value of a pe...
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Many learning systems search through a space of possible performance elements, seeking an element with high expected utility. As the task of nding the globally optimal element is usually intractable, many practical learning systems use hill-climbing to nd a local optimum. Unfortunately, even this is diicult, as it depends on the distribution of problems, which is typically unknown. This paper a...
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A toy optimisation problem is introduced which consists of a ÿtness gradient broken up by a series of hurdles. The performance of a hill-climber and a stochastic hill-climber are computed. These are compared with the empirically observed performance of a genetic algorithm (GA) with and without. The hill-climber with a suuciently large neighbourhood outperforms the stochastic hill-climber, but i...
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This paper presents a convergence analysis for the problem of consistent labelling using genetic search. The work builds on a recent empirical study of graph matching where we showed that a Bayesian consistency measure could be e$ciently optimised using a hybrid genetic search procedure which incorporated a hill-climbing step. In the present study we return to the algorithm and provide some the...
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ژورنال
عنوان ژورنال: Artificial Intelligence
سال: 1996
ISSN: 0004-3702
DOI: 10.1016/0004-3702(95)00040-2