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Learning and Reasoning in Unknown Domains

机译:未知领域中的学习和推理

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摘要

In the story Alice in Wonderland, Alice fell down a rabbit hole and suddenly found herself in a strange world called Wonderland. Alice gradually developed knowledge about Wonderland by observing, learning, and reasoning. In this paper we present the system Alice In Wonderland that operates analogously. As a theoretical basis of the system, we define several basic concepts of logic in a generalized setting, including the notions of domain, proof, consistency, soundness, completeness, decidability, and compositionality. We also prove some basic theorems about those generalized notions. Then we model Wonderland as an arbitrary symbolic domain and Alice as a cognitive architecture that learns autonomously by observing random streams of facts from Wonderland. Alice is able to reason by means of computations that use bounded cognitive resources. Moreover, Alice develops her belief set by continuously forming, testing, and revising hypotheses. The system can learn a wide class of symbolic domains and challenge average human problem solvers in such domains as propositional logic and elementary arithmetic.
机译:在故事《爱丽丝梦游仙境》中,爱丽丝掉下了兔子洞,突然发现自己身处一个名为“仙境”的陌生世界。爱丽丝通过观察,学习和推理逐渐发展了有关仙境的知识。在本文中,我们介绍了类似运行的系统“爱丽丝梦游仙境”。作为系统的理论基础,我们在广义的环境中定义了逻辑的几个基本概念,包括域,证明,一致性,健全性,完整性,可判定性和组合性的概念。我们还证明了有关那些广义概念的一些基本定理。然后,我们将Wonderland建模为任意符号域,并将Alice建模为认知架构,该架构通过观察来自Wonderland的随机事实流来自主学习。爱丽丝能够通过使用有限认知资源的计算来推理。此外,爱丽丝通过不断形成,检验和修改假设来发展自己的信念。该系统可以学习各种各样的符号领域,并在命题逻辑和基本算术等领域挑战普通的人类问题解决者。

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