Representations for a complex world: Combining distributed and localist representations for learning and planning

Autor(en): Bach, J
Herausgeber: Wermter, S
Palm, G
Elshaw, M
Stichwörter: Computer Science; Computer Science, Artificial Intelligence; Robotics
Erscheinungsdatum: 2005
Herausgeber: SPRINGER-VERLAG BERLIN
Journal: BIOMIMETIC NEURAL LEARNING FOR INTELLIGENT ROBOTS: INTELLIGENT SYSTEMS, COGNITIVE ROBOTICS, AND NEUROSCIENCE
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
Volumen: 3575
Startseite: 265
Seitenende: 280
Zusammenfassung: 
To have agents autonomously model a complex environment, it is desirable to use distributed representations that lend themselves to neural learning. Yet developing and executing plans acting on the environment calls for abstract, localist representations of events, objects and categories. To combine these requirements, a formalism that can express neural networks, action sequences and symbolic abstractions with the same means may be considered advantageous. We are currently exploring the use of compositional hierarchies that we treat both as Knowledge Based Artificial Neural Networks and as localist representations for plans and control structures. These hierarchies are implemented using MicroPsi node nets and used in the control of agents situated in a complex simulated environment.
Beschreibung: 
International AI Workshop on NeuroBotics, Ulm, GERMANY, SEP 20, 2004
ISBN: 9783540274407
ISSN: 03029743

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