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Computer Science > Artificial Intelligence

arXiv:1605.05676 (cs)
[Submitted on 18 May 2016]

Title:Towards information based spatiotemporal patterns as a foundation for agent representation in dynamical systems

Authors:Martin Biehl, Takashi Ikegami, Daniel Polani
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Abstract:We present some arguments why existing methods for representing agents fall short in applications crucial to artificial life. Using a thought experiment involving a fictitious dynamical systems model of the biosphere we argue that the metabolism, motility, and the concept of counterfactual variation should be compatible with any agent representation in dynamical systems. We then propose an information-theoretic notion of \emph{integrated spatiotemporal patterns} which we believe can serve as the basic building block of an agent definition. We argue that these patterns are capable of solving the problems mentioned before. We also test this in some preliminary experiments.
Comments: 8 pages, 3 figures
Subjects: Artificial Intelligence (cs.AI); Social and Information Networks (cs.SI)
MSC classes: 92B20
ACM classes: G.3; I.2.11; I.5.1; J.3
Cite as: arXiv:1605.05676 [cs.AI]
  (or arXiv:1605.05676v1 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.1605.05676
Journal reference: Proceedings of the Artificial Life Conference 2016
Related DOI: https://doi.org/10.7551/978-0-262-33936-0-ch115

Submission history

From: Martin Biehl [view email]
[v1] Wed, 18 May 2016 18:18:38 UTC (25 KB)
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