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Brain Theory from Artificial Life
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Brain Theory from Artificial Life

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".

Deadline for manuscript submissions: closed (20 February 2023) | Viewed by 11356

Special Issue Editors

Prof. Dr. Takashi Ikegami

E-Mail Website
Guest Editor
Graduate School of Arts and Sciences, University of Tokyo, Tokyo 153-8902, Japan
Interests: open-ended evolution; life–mind continuity; offloaded agency; complex systems; artificial life
Special Issues, Collections and Topics in MDPI journals
Dr. Hiroyuki Iizuka

E-Mail Website
Guest Editor
1. Faculty of Information Science and Technology, Hokkaido University, Hokkaido 060-0814, Japan
2. Center for Human Nature, Artificial Intelligence, and Neuroscience, Hokkaido University, Hokkaido 060-0812, Japan
Interests: artificial life; artificial intelligence; cognitive modeling
Dr. Keisuke Suzuki

E-Mail Website
Guest Editor
Center for Human Nature, Artificial Intelligence and Neuroscience, Hokkaido University, Hokkaido 060-0812, Japan
Interests: embodied cognition; bodily self-consciousness; virtual reality; sense of presence; computational neurophenomenology

Special Issue Information

Dear Colleagues,

The main theme of this Special Issue is brain theory from artificial life research. For the past three decades, brain theory in the field of artificial life has been discussed in terms of genetic algorithms, neural networks, chaos theory, and sensorimotor association.

However, with the recent development of cognitive and epistemological theories based on the development of deep neural networks and proposals, such as Friston's free-energy principle, research on artificial life is also developing.

In this Special Issue, we invite research that sheds light on new principles, techniques, and applications of brain theory, or, in other words, perception and corporeality from artificial life. In particular, we welcome research from new information-theoretic perspectives, such as Friston's free-energy principle, Tononi's integrated information theory, and empowerment theory.

Prof. Dr. Takashi Ikegami
Dr. Hiroyuki Iizuka
Dr. Keisuke Suzuki
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sensory-motor contingency
  • evolutionary theory
  • genetic algorithm
  • deep neural networks
  • chaos theory
  • free-energy principle
  • active inference
  • integrated information theory
  • empowerment

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Published Papers (2 papers)

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25 pages, 21310 KiB  
Article
Turn-Taking Mechanisms in Imitative Interaction: Robotic Social Interaction Based on the Free Energy Principle
by Nadine Wirkuttis, Wataru Ohata and Jun Tani
Entropy 2023, 25(2), 263; https://doi.org/10.3390/e25020263 - 31 Jan 2023
Cited by 5 | Viewed by 2700
Abstract
This study explains how the leader-follower relationship and turn-taking could develop in a dyadic imitative interaction by conducting robotic simulation experiments based on the free energy principle. Our prior study showed that introducing a parameter during the model training phase can determine leader [...] Read more.
This study explains how the leader-follower relationship and turn-taking could develop in a dyadic imitative interaction by conducting robotic simulation experiments based on the free energy principle. Our prior study showed that introducing a parameter during the model training phase can determine leader and follower roles for subsequent imitative interactions. The parameter is defined as w, the so-called meta-prior, and is a weighting factor used to regulate the complexity term versus the accuracy term when minimizing the free energy. This can be read as sensory attenuation, in which the robot’s prior beliefs about action are less sensitive to sensory evidence. The current extended study examines the possibility that the leader-follower relationship shifts depending on changes in w during the interaction phase. We identified a phase space structure with three distinct types of behavioral coordination using comprehensive simulation experiments with sweeps of w of both robots during the interaction. Ignoring behavior in which the robots follow their own intention was observed in the region in which both ws were set to large values. One robot leading, followed by the other robot was observed when one w was set larger and the other was set smaller. Spontaneous, random turn-taking between the leader and the follower was observed when both ws were set at smaller or intermediate values. Finally, we examined a case of slowly oscillating w in anti-phase between the two agents during the interaction. The simulation experiment resulted in turn-taking in which the leader-follower relationship switched during determined sequences, accompanied by periodic shifts of ws. An analysis using transfer entropy found that the direction of information flow between the two agents also shifted along with turn-taking. Herein, we discuss qualitative differences between random/spontaneous turn-taking and agreed-upon sequential turn-taking by reviewing both synthetic and empirical studies. Full article
(This article belongs to the Special Issue Brain Theory from Artificial Life)
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19 pages, 1722 KiB  
Hypothesis
Irruption Theory: A Novel Conceptualization of the Enactive Account of Motivated Activity
by Tom Froese
Entropy 2023, 25(5), 748; https://doi.org/10.3390/e25050748 - 2 May 2023
Cited by 13 | Viewed by 7589
Abstract
Cognitive science is lacking conceptual tools to describe how an agent’s motivations, as such, can play a role in the generation of its behavior. The enactive approach has made progress by developing a relaxed naturalism, and by placing normativity at the core of [...] Read more.
Cognitive science is lacking conceptual tools to describe how an agent’s motivations, as such, can play a role in the generation of its behavior. The enactive approach has made progress by developing a relaxed naturalism, and by placing normativity at the core of life and mind; all cognitive activity is a kind of motivated activity. It has rejected representational architectures, especially their reification of the role of normativity into localized “value” functions, in favor of accounts that appeal to system-level properties of the organism. However, these accounts push the problem of reification to a higher level of description, given that the efficacy of agent-level normativity is completely identified with the efficacy of non-normative system-level activity, while assuming operational equivalency. To allow normativity to have its own efficacy, a new kind of nonreductive theory is proposed: irruption theory. The concept of irruption is introduced to indirectly operationalize an agent’s motivated involvement in its activity, specifically in terms of a corresponding underdetermination of its states by their material basis. This implies that irruptions are associated with increased unpredictability of (neuro)physiological activity, and they should, hence, be quantifiable in terms of information-theoretic entropy. Accordingly, evidence that action, cognition, and consciousness are linked to higher levels of neural entropy can be interpreted as indicating higher levels of motivated agential involvement. Counterintuitively, irruptions do not stand in contrast to adaptive behavior. Rather, as indicated by artificial life models of complex adaptive systems, bursts of arbitrary changes in neural activity can facilitate the self-organization of adaptivity. Irruption theory therefore, makes it intelligible how an agent’s motivations, as such, can make effective differences to their behavior, without requiring the agent to be able to directly control their body’s neurophysiological processes. Full article
(This article belongs to the Special Issue Brain Theory from Artificial Life)
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