The essence of embodiment: A framework for understanding and exploiting structural coupling between system and environment

A framework for understanding and exploiting embodiment is presented which is not dependent on any specific ontological context. This framework is founded on a new definition of embodiment, based on the relational dynamics that exist between biological organisms and their environments, and inspired by the structural dynamics of the bacterium Escherichia coli. The definition draws on the idea of mutual perturbation between a system (biological organism, robot, or software agent) and its environment, enabling structural coupling between the two. The framework provides a vocabulary and concepts that can be used to discuss and analyze embodiment in any kind of environment, not just the material world. Rather than blurring boundaries between disciplines and domains, this permits the characterization of distinctions and common features between them, in a manner meaningful to all parties. Other benefits include the potential quantification of embodiment, and access to practical and theoretical ideas associated w...

[1]  Francisco J. Varela,et al.  Structural Coupling and the Origin of Meaning in a Simple Cellular Automation , 1988 .

[2]  T. Gelder,et al.  It's about time: an overview of the dynamical approach to cognition , 1996 .

[3]  S. Rose.  Lifelines: Biology, Freedom, Determinism , 1998 .

[4]  Hubert L. Dreyfus,et al.  What computers still can't do - a critique of artificial reason , 1992 .

[5]  Erich Prem,et al.  Epistemic Autonomy in Models of Living Systems , 1997 .

[6]  H. Maturana,et al.  Autopoiesis and Cognition , 1980 .

[7]  J. Crutchfield.  The calculi of emergence: computation, dynamics and induction , 1994 .

[8]  Filippo Menczer,et al.  From Complex Environments to Complex Behaviors , 1996, Adapt. Behav..

[9]  Oren Etzioni,et al.  Intelligence without Robots: A Reply to Brooks , 1993, AI Mag..

[10]  Christopher G. Langton,et al.  Studying artificial life with cellular automata , 1986 .

[11]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[12]  Richard K. Belewcmautner.  Testing Simulated Controllers in Real Robots , 1999 .

[13]  Christopher Landauer,et al.  Computational Embodiment: Constructing Autonomous Software Systems , 1999, Cybern. Syst..

[14]  Terry Winograd,et al.  Understanding computers and cognition , 1986 .

[15]  Maja J. Matarić,et al.  Behavior-Based Systems: Key Properties and Implications , 1992 .

[16]  J. Ross,et al.  A model of excitation and adaptation in bacterial chemotaxis. , 1995, Biophysical journal.

[17]  D. Bray,et al.  Computer simulation of the phosphorylation cascade controlling bacterial chemotaxis. , 1993, Molecular biology of the cell.

[18]  Chrystopher L. Nehaniv,et al.  Krohn-Rhodes theory, hierarchies & evolution , 1996, Mathematical Hierarchies and Biology.

[19]  Stefano Nolfi,et al.  Evolutionary Robotics: Exploiting the Full Power of Self-organization , 1998, Connect. Sci..

[20]  Randall D. Beer,et al.  A Dynamical Systems Perspective on Agent-Environment Interaction , 1995, Artif. Intell..

[21]  D. Bray,et al.  Origins of individual swimming behavior in bacteria. , 1998, Biophysical journal.

[22]  Tim Smithers,et al.  On quantitative performance measures of robot behaviour , 1995, Robotics Auton. Syst..

[23]  D. Bray,et al.  Receptor clustering as a cellular mechanism to control sensitivity , 1998, Nature.

[24]  Rolf Pfeifer,et al.  Cognition — Perspectives from Autonomous Agents , 1995 .

[25]  T. Gelder,et al.  Mind as Motion: Explorations in the Dynamics of Cognition , 1995 .

[26]  Rodney A. Brooks,et al.  Elephants don't play chess , 1990, Robotics Auton. Syst..

[27]  Peter J. Bentley,et al.  Three Ways to Grow Designs: A Comparison of Embryogenies for an Evolutionary Design Problem , 1999, GECCO.

[28]  R. K. Lindsay.  What Computers Can't Do. A Critique of Artificial Reason. Hubert L. Dreyfus. Harper and Row, New York, 1972. xxxvi, 260 pp. $8.95 , 1972 .

[29]  Stefano Nolfi,et al.  Evolving mobile robots in simulated and real environments , 1995 .

[30]  S. Wolfram.  Statistical mechanics of cellular automata , 1983 .

[31]  K. Dautenhahn,et al.  Arti(cid:12)cial Life and Natural Stories , 1998 .

[32]  Henrik Hautop Lund,et al.  Evolving and Breeding Robots , 1998, EvoRobot.

[33]  Stanley J. Rosenschein,et al.  A dynamical systems perspective on agent-environment interaction , 1996 .

[34]  H. Dreyfus.  Mind Over Machine , 1986 .

[35]  Richard K. Belew,et al.  Coupling morphology and control in a simulated robot , 1999 .

[36]  S. Leibler,et al.  Robustness in simple biochemical networks , 1997, Nature.

[37]  Hubert L. Dreyfus,et al.  The Current Relevance of Merleau-Ponty''s Phenomenology of Embodiment , 1996 .

[38]  R. Brooks.  Living Machines , 2001 .

[39]  Kerstin Dautenhahn,et al.  Biologically Inspired Robotic Experiments on Interaction and Dynamic Agent-Environment Couplings , 1997 .

[40]  J. S. Parkinson,et al.  A model of excitation and adaptation in bacterial chemotaxis. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[41]  Myra S. Wilson,et al.  Evolving hierarchical robot behaviours , 1997, Robotics Auton. Syst..

[42]  Randall D. Beer,et al.  The brain has a body: adaptive behavior emerges from interactions of nervous system, body and environment , 1997, Trends in Neurosciences.

[43]  Stan Franklin,et al.  Autonomous Agents as Embodied Ai , 1997, Cybern. Syst..