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Modeling the Role of Energy Management in Embodied Cognition
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The quest for adaptive and autonomous robots, flexible enough to smoothly comply with unstructured environments and operate in close interaction with humans, seems to require a deep rethinking of classical engineering methods. The adaptivity of natural organisms, whose cognitive capacities are rooted in their biological organization, is an obvious source of inspiration. While approaches that highlight the role of embodiment in both cognitive science and cognitive robotics are gathering momentum, the crucial role of internal bodily processes as foundational components of the biological mind is still largely neglected.

This thesis advocates a perspective on embodiment that emphasizes the role of non-neural bodily dynamics in the constitution of cognitive processes in both natural and artificial systems. In the first part, it critically examines the theoretical positions that have influenced current theories and the author's own position. The second part presents the author's experimental work, based on the computer simulation of simple robotic agents engaged in energy-related tasks. Proto-metabolic dynamics, modeled on the basis of actual microbial fuel cells for energy generation, constitute the foundations of a powerful motivational engine. Following a history of adaptation, proto-metabolic states bias the robot towards specific subsets of behaviors, viably attuned to the current context, and facilitate a swift re-adaptation to novel tasks. Proto-metabolic dynamics put the situated nature of the agent-environment sensorimotor interaction within a perspective that is functional to the maintenance of the robot's overall `survival'. Adaptive processes tend to convert metabolic constraints into opportunities, branching into a rich and energetically viable behavioral diversity.

Place, publisher, year, edition, pages
Linköping University Electronic Press, 2012. , 116 p.
Series
Linköping Studies in Science and Technology, ISSN 0345-7524 ; 1455
National Category
Computer and Information Science
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-6887ISBN: 978-91-7519-882-8 OAI: oai:DiVA.org:his-6887DiVA: diva2:574389
Note

Delarbeten:

1: Montebelli, A., Herrera, C. and Ziemke, T. (2008) On Cognition as Dynamical Coupling: An Analysis of Behavioral Attractor Dynamics, Adaptive Behavior, 16(2-3), pp. 182-195.

2: Montebelli, A., Ieropoulos, I., Lowe, R., Ziemke, T., Melhuish, C. and Greenman, J. An Oxygen-Diffusion Cathode MFC Model for Simulation of Energy-Autonomous Robots. (Manuskript (preprint))

3: Montebelli, A., Lowe, R., Ieropoulos, I., Melhuish, C., Greenman, J. and Ziemke, T. (2010) Microbial Fuel Cell Driven Behavioral Dynamics in Robot Simulations. In Artificial Life XII. Proceedings of the Twelfth International Conference on the Synthesis and Simulation of Living Systems, pp. 749-756.

4: Montebelli, A., Lowe, R. and Ziemke, T. Towards Metabolic Robotics: Insights from Modeling Embodied Cognition in a Bio-mechatronic symbiont. (Manuskript (preprint))

5: Montebelli, A., Lowe, R. and Ziemke, T. (2003) The Cognitive Body: from Dynamic Modulation to Anticipation. In Anticipatory Behavior in Adaptive Learning Systems: Foundations, Theories, and Systems. Lecture Notes in Artivicial Intelligence, 2003:X, pp. 132-151.

6: Montebelli, A., Lowe, R. and Ziemke, T. (2010) More from the Body: Embodied anticipation for swift re-adaptation in neurocomputational cognitive architectures for robotic agents. In Advances in Cognitive Systems: Foundation, Theories, and Systems. pp. 249-270.

Available from: 2012-12-28 Created: 2012-12-05 Last updated: 2015-10-29Bibliographically approved
List of papers
1. On Cognition as Dynamical Coupling: An Analysis of Behavioral Attractor Dynamics
Open this publication in new window or tab >>On Cognition as Dynamical Coupling: An Analysis of Behavioral Attractor Dynamics
2008 (English)In: Adaptive Behavior, ISSN 1059-7123, E-ISSN 1741-2633, Vol. 16, no 2-3, 182-195 p.Article in journal (Refereed) Published
Abstract [en]

The interaction of brain, body, and environment can result incomplex behavior with rich dynamics, even for relatively simpleagents. Such dynamics are, however, often difficult to analyze.In this article, we explore the case of a simple simulated roboticagent, equipped with a reactive neurocontroller and an energylevel, which the agent has been evolved to recharge. A dynamicalsystems analysis shows that a non-neural internal state (energylevel), despite its simplicity, dynamically modulates the behavioralattractors of the agent—environment system, such thatthe robot's behavioral repertoire is continually adapted toits current situation and energy level. What emerges is a dynamic,non-deterministic, and highly self-organized action selectionmechanism, originating from the dynamical coupling of four systems(non-neural internal states, neurocontroller, body, and environment)operating at very different timescales.

Place, publisher, year, edition, pages
Sage Publications, 2008
Keyword
evolutionary robotics, dynamical systems, embodied cognition, internal robotics, neuromodulation
National Category
Psychology (excluding Applied Psychology)
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-2764 (URN)10.1177/1059712308089180 (DOI)000254521600007 ()2-s2.0-40749134570 (Scopus ID)
Available from: 2009-02-18 Created: 2009-02-18 Last updated: 2015-10-29Bibliographically approved
2. Microbial fuel cell driven behavioural dynamics in robot simulations
Open this publication in new window or tab >>Microbial fuel cell driven behavioural dynamics in robot simulations
Show others...
2010 (English)In: Artificial Life XII: Proceedings of the Twelfth International Conference on the Synthesis and Simulation of Living Systems / [ed] Harold Fellermann, Mark Dörr, Martin Hanczyc, Lone Ladegaard Laursen, Sarah Maurer, Daniel Merkle, Pierre-Alain Monnard, Kasper Støy, Steen Rasmussen, Cambridge, Massachusetts: MIT Press, 2010, 749-756 p.Conference paper, (Refereed)
Abstract [en]

With the present study we report the first application of a recently proposed model for realistic microbial fuel cells (MFCs) energy generation dynamics, suitable for robotic simulations with minimal and extremely limited computational overhead. A simulated agent was adapted in order to engage in a viable interaction with its environment. It achieved energy autonomy by maintaining viable levels of the critical variables of MFCs, namely cathodic hydration and anodic substrate biochemical energy. After unsupervised adaptation by genetic algorithm, these crucial variables modulate the behavioral dynamics expressed by viable robots in their interaction with the environment. The analysis of this physically rooted and self-organized dynamic action selection mechanism constitutes a novel practical contribution of this work. We also compare two different viable strategies, a self-organized continuous and a pulsed behavior, in order to foresee the possible cognitive implications of such biologicalmechatronics hybrid symbionts in a novel scenario of ecologically grounded energy and motivational autonomy.

Place, publisher, year, edition, pages
Cambridge, Massachusetts: MIT Press, 2010
National Category
Computer and Information Science
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-4813 (URN)978-0-262-29075-3 (ISBN)0-262-29075-8 (ISBN)
Conference
Twelfth International Conference on the Synthesis and Simulation of Living Systems, 19th - 23rd August, 2010, Odense, Denmark
Available from: 2011-04-12 Created: 2011-04-12 Last updated: 2015-10-29Bibliographically approved
3. The Cognitive Body: From Dynamic Modulation to Anticipation
Open this publication in new window or tab >>The Cognitive Body: From Dynamic Modulation to Anticipation
2009 (English)In: Anticipatory Behavior in Adaptive Learning Systems, ABiALS 2008: From Psychological Theories to Artificial Cognitive Systems / [ed] Giovanni Pezzulo, Martin V. Butz, Olivier Sigaud, Gianluca Baldassarre, Berlin, Heidelberg: Springer Berlin/Heidelberg, 2009, 132-151 p.Conference paper, (Refereed)
Abstract [en]

Starting from the situated and embodied perspective on the study of cognition as a source of inspiration, this paper programmatically outlines a path towards an experimental exploration of the role of the body in a minimal anticipatory cognitive architecture. Cognition is here conceived and synthetically analyzed as a broadly extended and distributed dynamic process emerging from the interplay between a body, a nervous system and their environment. Firstly, we show how a non-neural internal state, crucially characterized by slowly changing dynamics, can modulate the activity of a simple neurocontroller. The result, emergent from the use of a standard evolutionary robotic simulation, is a selforganized, dynamic action selection mechanism, effectively operating in a context dependent way. Secondly, we show how these characteristics can be exploited by a novel minimalist anticipatory cognitive architecture. Rather than a direct causal connection between the anticipationprocess and the selection of the appropriate behavior, it implements a model for dynamic anticipation that operates via bodily mediation (bodily-anticipation hypothesis). This allows the system to swiftly scale up to more complex tasks never experienced before, achieving flexible and robust behavior with minimal adaptive cost.

Place, publisher, year, edition, pages
Berlin, Heidelberg: Springer Berlin/Heidelberg, 2009
Series
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743 ; 5499 LNAI
National Category
Computer and Information Science
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-3538 (URN)10.1007/978-3-642-02565-5_8 (DOI)000269259700008 ()2-s2.0-70349314535 (Scopus ID)978-3-642-02564-8 (ISBN)
Conference
The 4th Workshop on Anticipatory Behavior in Adaptive Learning Systems (ABiALS 2008), Munich, June 26–27, 2008
Note

The original publication is available at www.springerlink.com

Available from: 2010-01-07 Created: 2010-01-07 Last updated: 2015-10-29Bibliographically approved

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