Anytime bounded rationality

Eric Nivel, Kristinn R. Thórisson, Bas Steunebrink, Jürgen Schmidhuber

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

Dependable cyber-physical systems strive to deliver anticipative, multi-objective performance anytime, facing deluges of inputs with varying and limited resources. This is even more challenging for life-long learning rational agents as they also have to contend with the varying and growing know-how accumulated from experience. These issues are of crucial practical value, yet have been only marginally and unsatisfactorily addressed in AGI research. We present a value-driven computational model of anytime bounded rationality robust to variations of both resources and knowledge. It leverages continually learned knowledge to anticipate, revise and maintain concurrent courses of action spanning over arbitrary time scales for execution anytime necessary.
Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlagservice@springer.de
Pages121-130
Number of pages10
ISBN (Print)9783319213644
DOIs
StatePublished - Jan 1 2015
Externally publishedYes

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