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arXiv 1109.0774cs.PL
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Haskell中基于自适应的编程

Adaptation-Based Programming in Haskell

Tim Bauer, Martin Erwig, Alan Fern, Jervis Pinto

摘要:

我们提出了一个嵌入式DSL,以支持基于自适应编程(ABP)在Haskell。ABP是一个抽象的模型,用于定义自适应值,称为自适应值,它根据一些相关的反馈进行调整。我们展示了我们在Haskell中的设计选择如何激励更高级别的组合子和构造,并帮助我们获得更复杂的组合自适应。我们还展示了ABP的一个重要专业化是支持强化学习结构,它根据程序员指定的目标函数优化自适应值。这使得ABP用户可以轻松地定义自适应值,以表达其程序中任何地方的不确定性。在重复执行过程中,这些自适应值会调整为更有效的值,并使用户的程序能够自我优化。我们的DSL的设计很大程度上依赖于类型类的使用。在介绍DSL的同时,我们还将举例说明类型类的使用如何支持DSL的逐步发展。

英文摘要:

We present an embedded DSL to support adaptation-based programming (ABP) in Haskell. ABP is an abstract model for defining adaptive values, called adaptives, which adapt in response to some associated feedback. We show how our design choices in Haskell motivate higher-level combinators and constructs and help us derive more complicated compositional adaptives. We also show an important specialization of ABP is in support of reinforcement learning constructs, which optimize adaptive values based on a programmer-specified objective function. This permits ABP users to easily define adaptive values that express uncertainty anywhere in their programs. Over repeated executions, these adaptive values adjust to more efficient ones and enable the user's programs to self optimize. The design of our DSL depends significantly on the use of type classes. We will illustrate, along with presenting our DSL, how the use of type classes can support the gradual evolution of DSLs.

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