Literature DB >> 22120547

Perception-action loops of multiple agents: informational aspects and the impact of coordination.

Philippe Capdepuy1, Daniel Polani, Chrystopher L Nehaniv.   

Abstract

Embodied agents can be conceived as entities perceiving and acting upon an external environment. Probabilistic models of this perception-action loop have paved the way to the investigation of information-theoretic aspects of embodied cognition. This formalism allows (i) to identify information flows and their limits under various scenarios and constraints, and (ii) to use informational quantities in order to induce the self-organization of the agent's behavior without any externally specified drives. This article extends the perception-action loop formalism to multiple agents. The multiple-access channel model is presented and used to identify the relationships between informational quantities of two agents interacting in the same environment. The central question investigated in this article is the impact of coordination. Information-theoretic limits on what can be achieved with and without coordination are identified. For this purpose, different abstract channels are studied, along with a concrete example of agents interacting in space. It is shown that, under some conditions, self-organizing systems based on information-theoretic quantities have a tendency to spontaneously generate coordinated behavior. Moreover, in the perspective of engineering such systems to achieve specific tasks, these information-theoretic limits put constraints on the amount of coordination that is required to perform the task, and consequently on the mechanisms that underlie self-organization in the system.

Mesh:

Year:  2011        PMID: 22120547     DOI: 10.1007/s12064-011-0143-y

Source DB:  PubMed          Journal:  Theory Biosci        ISSN: 1431-7613            Impact factor:   1.919


  3 in total

1.  Information-theoretic limits of control

Authors: 
Journal:  Phys Rev Lett       Date:  2000-02-07       Impact factor: 9.161

2.  Representations of space and time in the maximization of information flow in the perception-action loop.

Authors:  Alexander S Klyubin; Daniel Polani; Chrystopher L Nehaniv
Journal:  Neural Comput       Date:  2007-09       Impact factor: 2.026

3.  Mapping information flow in sensorimotor networks.

Authors:  Max Lungarella; Olaf Sporns
Journal:  PLoS Comput Biol       Date:  2006-10-27       Impact factor: 4.475

  3 in total
  2 in total

1.  Guided self-organization: perception-action loops of embodied systems.

Authors:  Nihat Ay; Ralf Der; Mikhail Prokopenko
Journal:  Theory Biosci       Date:  2012-09       Impact factor: 1.919

2.  Intrinsically motivated collective motion.

Authors:  Henry J Charlesworth; Matthew S Turner
Journal:  Proc Natl Acad Sci U S A       Date:  2019-07-17       Impact factor: 11.205

  2 in total

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