The DOI matches its Crossref record.
Exploring Robotic Minds: Actions, Symbols, and Consciousness as Self-Organizing Dynamic Phenomena
Abstract
Abstract How do “minds” work? In Exploring Robotic Minds: Actions, Symbols, and Consciousness as Self-Organizing Dynamic Phenomena, Professor Jun Tani reviews key experiments within his own pioneering neurorobotics research project aimed at answering this fundamental and fascinating question. The book shows how symbols and concepts representing the world can emerge via “deep learning” within robots, by using specially designed neural network architectures by which, given iterative interactions between top-down proactive “subjective” and “intentional” processes for plotting action, and bottom-up updates of the perceptual reality after action, the robot is able to learn to isolate, to identify, and even to infer salient features of the operational environment, modifying its behavior based on anticipations of both objective and social cues. Through permutations of this experimental model, the book then argues that longstanding questions about the nature of “consciousness” and “freewill” can be addressed through an understanding of the dynamic structures within which, in the course of normal operations and in a changing operational environment, necessary top-down/bottom-up interactions arise. Written in clear and accessible language, this book opens a privileged window for a broad audience onto the science of artificial intelligence and the potential for artificial consciousness, threading cognitive neuroscience, dynamic systems theory, robotics, and phenomenology through an elegant series of deceptively simple experiments that build upon one another and ultimately outline the fundamental form of the working mind.
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“Further, deep internal dynamics create a potential for functional decoupling between modeling and the unfolding of particular sensorimotor engagements (Tani, 2016; Sormaz et al., 2018; Corcoran et al., 2020), thus enabling counterfactual simulations (Kanai et al., 2019) with temporal “thickness”/“depth” (Humphrey, 2017; Friston, 2018), which when conscious enable imagination and explicit planning.”
From An Integrated World Modeling Theory (IWMT) of Consciousness (2020) · cites this paper as Tani, 2016
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Items 101–115 of 115
Philosophy of Embodied Mind and Intelligent Robotics
Kureha, M. (2021) · Journal of the Robotics Society of Japan · doi:10.7210/jrsj.39.28
Rethinking (Supreme?) Robotics
Asada, M. (2021) · Journal of the Robotics Society of Japan · doi:10.7210/jrsj.39.45
RSAC: Regularized Subspace Approximation Classifier for Lightweight Continuous Learning
Ho, C.-H., & Tsai, S.-H. L. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9413025
Asada, M. (2021) · Springer eBooks · doi:10.1007/978-3-642-41610-1_200-1
Tani, J. (2022) · Springer eBooks · doi:10.1007/978-3-642-41610-1_204-1
Self-citationGradient Expectations: Structure, Origins, and Synthesis of Predictive Neural Networks
Downing, K. L. (2023) · The MIT Press eBooks · doi:10.7551/mitpress/14723.001.0001
Computational Modeling in Various Cognitive Fields
(2023) · Cambridge University Press eBooks · doi:10.1017/9781108755610.027
Studies of Cognitive Neurorobotics Based on the Free Energy Principle
Tani, J. (2023) · Journal of the Robotics Society of Japan · doi:10.7210/jrsj.41.609
Self-citationYadav, P. S. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5330026
Is mental content an illusion?
Facchin, M. (2025) · Synthese · doi:10.1007/s11229-025-05243-9
Recursive identity and ethical recognition in humans, robots, and AI
Sawyer, C. H. (2026) · AI & Society · doi:10.1007/s00146-026-02943-9
Human-Machine Collaboration Dynamics - A Sustainable AI Perspective
Kozma, R., & Rudas, I. (2026) · International Conference on Advances in Artificial Intelligence and Machine Learning (AAIML) · doi:10.1109/aaiml67890.2026.11498133
System 0/1/2/3: Quad-Process Theory of Collective Cognitive Systems
Taniguchi, T. (2026) · Journal of the Robotics Society of Japan · doi:10.7210/jrsj.44.441
Tanaka, S. (2026) · Neuroscience of Consciousness · doi:10.1093/nc/niag032
Klimaj, V., & Safron, A. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-33010-9_28
Metadata
- Authors
- Tani, J.
- Corresponding author
- Tani, Jun
- ORCID
- Tani, Jun
- Venue
- Oxford University Press eBooks
- Publisher
- Oxford University Press
- Published
- 2016-12-23
- OpenAlex
- W2553496799
- Cited by
- 116
- References
- 0
- Citations by year
- 2026: 8 · 2025: 7 · 2024: 9 · 2023: 16 · 2022: 8 · 2021: 14 · 2020: 17 · 2019: 15 · 2018: 13 · 2017: 8
- FWCI
- 6.29
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Oxford University Press eBooks (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Embodied and Extended Cognition
- Physical Sciences › Computer Science › Artificial Intelligence › Psychiatry, Mental Health, Neuroscience
- Social Sciences › Arts and Humanities › Philosophy › Philosophy and Theoretical Science
- Keywords
- neurorobotics, artificial consciousness, free will, self-organization, dynamical systems theory, intentionality, anticipatory behavior, social cues, phenomenology, cognitive neuroscience, robot cognition
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.