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Editors’ Introduction

机译:编辑介绍

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摘要

The conference “Algorithmic Learning Theory 2006” is dedicated to studies of learning from a mathematical and algorithmic perspective. Researchers consider various abstract models of the problem of learning and investigate how the learning goal in such a setting can be formulated and achieved. These models describe ways to define – the goal of learning, – how the learner retrieves information about its environment, – how to form of the learner’s models of the world (in some cases). Retrieving information is in some models is passive where the learner just views a stream of data. In other models, the learner is more active, asking questions or learning from its actions. Besides explicit formulation of hypotheses in an abstract language with respect to some indexing system, there are also more implicit methods like making predictions according to the current hypothesis on some arguments which then are evaluated with respect to their correctness and wrong predictions (coming from wrong hypotheses) incur
机译:会议“算法学习理论2006”致力于从数学和算法的角度学习学习。研究人员考虑各种抽象模型的学习问题,并调查这种设置中的学习目标如何制定和实现。这些模型描述了定义的方法 - 学习的目标 - 学习者如何检索有关其环境的信息, - 如何形成世界学习者的模型(在某些情况下)。检索信息在某些型号中是被动的,其中学习者只是观看数据流。在其他模型中,学习者更加积极,提出问题或从其行动中学习。除了关于一些索引系统中的抽象语言中的假设的明确制定外,还有更具隐含的方法,例如根据当前假设对一些参数进行预测,然后对其正确性和错误的预测进行评估(来自错误的假设)招致

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