Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/75599
Title: Controlling combinatorial explosion in inference via synergy with nonlinear-dynamical attention allocation
Authors: Goertzel, B
Belachew, MB 
Ikle, M
Yu, GN 
Issue Date: 2016
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2016, v. 9782, p. 334-343 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: One of the core principles of the OpenCog AGI design, "cognitive synergy", is exemplified by the synergy between logical reasoning and attention allocation. This synergy centers on a feedback in which nonlinear-dynamical attention-spreading guides logical inference control, and inference directs attention to surprising new conclusions it has created. In this paper we report computational experiments in which this synergy is demonstrated in practice, in the context of a very simple logical inference problem. More specifically: First-order probabilistic inference generates conclusions, and its inference steps are pruned via "Short Term importance" (STI) attention values associated to the logical Atoms it manipulates. As inference generates conclusions, information theory is used to assess the surprisingness value of these conclusions, and the "short term importance" attention values of the Atoms representing the conclusions are updated accordingly. The result of this feedback is that meaningful conclusions are drawn after many fewer inference steps than would be the case without the introduction of attention allocation dynamics and feedback therewith. This simple example demonstrates a cognitive dynamic that is hypothesized to be very broadly valuable for general intelligence.
Description: 9th International Conference on Artificial General Intelligence (AGI) Held as Part of Joint Multi-Conference on Human-Level Intelligence (HLAI), Jul 16-19, 2016, New York City, NY, US
URI: http://hdl.handle.net/10397/75599
ISBN: 978-3-319-41649-6
978-3-319-41648-9
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-319-41649-6_34
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