By Ahmed M. H. Abdel-Fattah, Ulf Krumnack, Kai-Uwe Kühnberger (auth.), Kai-Uwe Kühnberger, Sebastian Rudolph, Pei Wang (eds.)
This publication constitutes the refereed lawsuits of the sixth foreign convention on synthetic basic Intelligence, AGI 2013, held in Beijing, China, in July/August 2013. The 23 papers (17 complete papers, three technical communications, and three specified consultation papers) have been rigorously reviewed and chosen from a number of submissions. the quantity collects the present learn endeavors dedicated to increase formalisms, algorithms, and versions, in addition to platforms which are certain at common intelligence. just like the predecessor AGI meetings, researchers proposed diversified methodologies and strategies as a way to bridge the space among types of really expert intelligence and common intelligence.
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Additional info for Artificial General Intelligence: 6th International Conference, AGI 2013, Beijing, China, July 31 – August 3, 2013 Proceedings
The only exceptions would be AGI systems constituting very close emulation of human brains or minds; and the pursuit of such systems is not currently central to the AGI ﬁeld. Yet, natural or not, understanding of human language is obviously critical to any AGI system that wants to interact ﬂexibly in the human world, and/or that wants to ingest the vast corpus of knowledge that humans have created and recorded. The problem of endowing AGI systems with understanding of human language, and human commonsense knowledge, presents a bit of a ”chicken and egg” problem.
We are speciﬁcally interested in Φ which are “data focusable” in the sense that, for a large number of highly ﬁt programs, there is a non-trivially large set Sf that is subset of Sand such that the ﬁtness score of f depends only on the restriction of f to Sf . What it is exactly to say that f depends only on its Integrating Feature Selection into Program Learning 35 restriction to f might be deﬁned in various sensible ways, for example saying that the ﬁtness score of f would be the same as the ﬁtness score of the program g that behaves just like f in Sf but always returns value zero outside of Sf .
For DeSTIN code see 3 . These two systems were not originally designed to work together, but we will describe a method for achieving their tight integration. com/tpsjr7/destin_ted_temp 42 B. Goertzel, T. Sanders, and J. O’Neill will not, however, describe either of the systems in any detail. The reader is referred to the above references, or for a quick review, to the online review of DeSTIN/OpenCog integration available at the URL 4 . One particular aspect of OpenCog is especially relevant here.
Artificial General Intelligence: 6th International Conference, AGI 2013, Beijing, China, July 31 – August 3, 2013 Proceedings by Ahmed M. H. Abdel-Fattah, Ulf Krumnack, Kai-Uwe Kühnberger (auth.), Kai-Uwe Kühnberger, Sebastian Rudolph, Pei Wang (eds.)