Solving a Problem With or Without a Program

Wang, Pei

doi:10.2478/v10229-011-0021-5

Cited by 2 publications

(1 citation statement)

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“…Among all possible compounds, which ones will be actually formed also depends on the system’s experience, like skill acquisition in humans. NARS has the ability of self-programming, in the sense that the system can organize its atomic operations into compound operations recursively and use them as a whole, so as to avoid repeated planning or searching (Wang, 2012b ). In this aspect, NARS is similar to the “recursive self-improvement” model in the study by Steunebrink et al ( 2016 ).…”

Section: Comparisons and Discussionmentioning

confidence: 99%

Self in NARS, an AGI System

Wang

Hammer

2018

Front. Robot. AI

Self Cite

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This article describes and discusses the self-related mechanisms of a general-purpose intelligent system, NARS. This system is designed to be adaptive and to work with insufficient knowledge and resources. The system's various cognitive functions are uniformly carried out by a central reasoning-learning process following a "non-axiomatic" logic. This logic captures the regularities of human empirical reasoning, where all beliefs are revisable according to evidence, and the meaning of concepts are grounded in the system's experience. NARS perceives its internal environment basically in the same way as how it perceives its external environment although the sensors involved are completely different. Consequently, its self-knowledge is mostly acquired and constructive, while being incomplete and subjective. Similarly, self-control in NARS is realized using mental operations, which supplement and adjust the automatic inference control routine. It is argued that a general-purpose intelligent system needs the notion of a "self," and the related knowledge and functions are developed gradually according to the system's experience. Such a mechanism has been implemented in NARS in a preliminary form.

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Section: Comparisons and Discussionmentioning

confidence: 99%