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Microbial Fuel Cell Driven Behavioral Dynamics in Robot Simulations

Alberto Montebelli, Robert Lowe, Ioannis Ieropoulos, Chris Melhuish, John Greenman, Tom Ziemke

Year
2010
Citations
12

Abstract

<p>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 biological-mechatronics hybrid symbionts in a novel scenario of ecologically grounded energy and motivational autonomy.</p>

Keywords

Microbial fuel cellRobotDynamics (music)Computer scienceArtificial intelligenceBiological systemSimulationEnvironmental scienceBiologyChemistry

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