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Synchronisation effects on the behavioural performance and information dynamics of a simulated minimally cognitive robotic agent

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BIOLOGICAL CYBERNETICS 2012年第6-7期106卷 407-427页

作者： Moioli, Renan C. Vargas, Patricia A. Husbands, Phil Univ Sussex CCNR Dept Informat Brighton BN1 9QH E Sussex England Heriot Watt Univ Sch Math & Comp Sci Edinburgh EH14 4AS Midlothian Scotland

Oscillatory activity is ubiquitous in nervous systems, with solid evidence that synchronisation mechanisms underpin cognitive processes. Nevertheless, its informational content and relationship with behaviour are still to be fully understood. In addition, cognitive systems cannot be properly appreciated without taking into account brain-body- environment interactions. In this paper, we developed a model based on the Kuramoto Model of coupled phase oscillators to explore the role of neural synchronisation in the performance of a simulated robotic agent in two different minimally cognitive tasks. We show that there is a statistically significant difference in performance and evolvability depending on the synchronisation regime of the network. In both tasks, a combination of information flow and dynamical analyses show that networks with a definite, but not too strong, propensity for synchronisation are more able to reconfigure, to organise themselves functionally and to adapt to different behavioural conditions. The results highlight the asymmetry of information flow and its behavioural correspondence. Importantly, it also shows that neural synchronisation dynamics, when suitably flexible and reconfigurable, can generate minimally cognitive embodied behaviour.

关键词： Synchronisation evolutionary robotics Oscillatory networks Transfer entropy Kuramoto model

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Automatic Design and Manufacture of Soft Robots

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IEEE TRANSACTIONS ON robotics 2012年第2期28卷 457-466页

作者： Hiller, Jonathan Lipson, Hod Cornell Univ Sibley Sch Mech & Aerosp Engn Ithaca NY 14853 USA

We present the automated design and manufacture of static and locomotion objects in which functionality is obtained purely by the unconstrained 3-D distribution of materials. Recent advances in multimaterial fabrication techniques enable continuous shapes to be fabricated with unprecedented fidelity unhindered by spatial constraints and homogeneous materials. We address the challenges of exploitation of the freedom of this vast new design space using evolutionary algorithms. We first show a set of cantilever beams automatically designed to deflect in arbitrary static profiles using hard and soft materials. These beams were automatically fabricated, and their physical performance was confirmed within 0.5-7.6% accuracy. We then demonstrate the automatic design of freeform soft robots for forward locomotion using soft volumetrically expanding actuator materials. One robot was fabricated automatically and assembled, and its performance was confirmed with 15% error. We suggest that this approach to design automation opens the door to leveraging the full potential of the freeform multimaterial design space to generate novel mechanisms and deformable robots.

关键词： Design automation evolutionary robotics soft robotics

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Behavioral robustness: An emergent phenomenon by means of distributed mechanisms and neurodynamic determinacy

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BIOSYSTEMS 2012年第1期107卷 34-51页

作者： Fernandez-Leon, Jose A. Univ Sussex CCNR Brighton BN1 9QG E Sussex England

Theoretical discussions and computational models of bio-inspired embodied and situated agents are introduced in this article capturing in simplified form the dynamical essence of robust, yet adaptive behavior. This article analyzes the general problem of how the dynamical coupling between internal control (brain), body and environment is used in the generation of specific behaviors. Based on the evolutionary robotics (ER) paradigm, four computational models are described to support discussions including descriptions on performance after a series of structural, sensorimotor or mutational perturbations, or are developed in the absence of them. Experimental results suggest that 'dynamic determinacy' - i.e. the continuous presence of a unique dynamical attractor that must be chased during functional behaviors - is a common dynamic phenomenon in the analyzed robust and adaptive agents. These agents show dynamical states that are definitely and unequivocally characterized via transient dynamics toward a unique, yet moving attractor at neural level for coherent actions. This determinacy emerges as a control strategy rooted on behavioral couplings and relies on mechanisms that are distributed on brain, body and environment. Different ways to induce further distribution of behavioral mechanisms are also discussed in this paper from a bio-inspired ER perspective. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

关键词： Behavioral robustness Bio-inspired theoretical biology evolutionary robotics Genetic algorithm Minimal cognition Complex adaptive systems

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Exploring and Evolving Process-oriented Control for Real and Virtual Fire Fighting Robots 12

Exploring and Evolving Process-oriented Control for Real and...

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14th International Conference on Genetic and evolutionary Computation Conference (GECCO)

作者： Hardey, Kathryn Corapcioglu, Eren Mattis, Molly Goadrich, Mark Jadud, Matthew Centenary Coll Louisiana Shreveport LA 71104 USA

ISBN: (纸本)9781450311779

Current research in evolutionary robotics is largely focused on creating controllers by either evolving neural networks or refning genetic programs based on grammar trees. We propose the use of the dataow languages for the construction of effective robotic controllers and the evolution of new controllers using genetic programming techniques. These languages have the advantages of being built on concurrent execution frameworks that lend themselves to formal verification along with being visualized as a dataow graph. In this paper, we compare and contrast the development and subsequent evolution of one such process-oriented control algorithm. Our control software was built from compos-able, communicating processes executing in parallel, and we tested our solution in an annual fire-fighting robotics competition. Subsequently, we evolved new controllers in a virtual simulation of this parallel dataow domain, and in doing so discovered and quantified more efficient solutions. This research demonstrates the effectiveness of using process networks as the basis for evolutionary robotics.

关键词： evolutionary robotics Concurreny CSP occam-pi

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On the Relationship Between Environmental and Morphological Complexity in Evolved Robots 12

On the Relationship Between Environmental and Morphological ...

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14th International Conference on Genetic and evolutionary Computation Conference (GECCO)

作者： Auerbach, Joshua E. Bongard, Josh C. Univ Vermont Dept Comp Sci Morphol Evolut & Cognit Lab Burlington VT 05401 USA

ISBN: (纸本)9781450311779

The principles of embodied cognition dictate that intelligent behavior must arise out of the coupled dynamics of an agent's brain, body, and environment. While the relationship between controllers and morphologies (brains and bodies) has been investigated, little is known about the interplay between morphological complexity and the complexity of a given task environment. It is hypothesized that the morphological complexity of a robot should increase commensurately with the complexity of its task environment. Here this hypothesis is tested by evolving robot morphologies in a simple environment and in more complex environments. More complex robots tend to evolve in the more complex environments lending support to this hypothesis. This suggests that gradually increasing the complexity of task environments may provide a principled approach to evolving more complex robots.

关键词： evolutionary robotics Morphological Complexity

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Evo-Devo-Robo Workshop Program 12

Evo-Devo-Robo Workshop Program

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14th International Conference on Genetic and evolutionary Computation Conference (GECCO)

作者： Doncieux, Stephane Jin, Yaochu Mouret, Jean-Baptiste Univ Pierre & Marie Curie Paris 6 ISIR CNRS UMR 7222 Paris France Univ Surrey Dept Comp Guildford Surrey England

ISBN: (纸本)9781450311786

Developmental robotics (also known as epigenctic robotics) is mainly concerned with modeling the postnatal develop ment of cognitive behaviors in living systems, such as language, cmotion, curiosity, anticipation, and social skills. While current work in this field has shown significant successes, we believe integrating research on developmental (including epigenctic and morphogenctic) robotics and evolutionary robotics is the natural next step. This workshop aims at bringing together evolutionary robotics and developmental robotics to form a new research area "evolutionary developmental robotics" (evo-devo-robo). The present paper contains the abstracts of the talks given by each of the seven invited speakers. These abstracts cover research in both fields and give an overview of the potential interactions between developmental and evolutionary robotics.

关键词： evolutionary Algorithm evolutionary robotics Neuro-Evolution Behavior Exploration Diversity Novelty

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Leveraging Multiple Simulators for Crossing the Reality Gap

Leveraging Multiple Simulators for Crossing the Reality Gap

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12th International Conference on Control, Automation, robotics and Vision (ICARCV)

作者： Boeing, A. Braeunl, T. Univ Western Australia Sch Elect Elect & Comp Engn Perth WA 6009 Australia

ISBN: (纸本)9781467318723;9781467318716

We propose a novel approach for transferring evolved control systems from a simulated environment to a real robot. Multiple dynamic simulation systems are simultaneously employed to provide a valid range of simulation variance that can be exploited to generate robust controllers in a purely virtual environment. These controllers can then be directly transferred to a physical robot.

关键词： simulation evolution robot reailty gap evolutionary robotics AUV fluid dynamics

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Dynamic Behavioral Diversity 12

Dynamic Behavioral Diversity

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14th International Conference on Genetic and evolutionary Computation Conference (GECCO)

作者： Doncieux, Stephane Mouret, Jean-Baptiste Univ Pierre & Marie Curie Paris 6 ISIR CNRS UMR 7222 4 Pl Jussieu F-75252 Paris 05 France

ISBN: (纸本)9781450311786

Behavioral Diversity (BD) aims at improving the evolution of robots by fostering exploration on the basis of their behavior, whereas evolutionary algorithms typically consider the diversity on a genotypic level. Several Behavioral Similarity Measures (BSM), the key component to improve behavioral diversity, have been investigated in the litterature. Current benchmarks show that (1) most tested BSM improve the final performance, (2) they do not lead to the same improvements and, (3) it is hard to predict a priori which BSM will work the best. Instead of trying to find the best BSM, a different approach is proposed here: assuming that several BSM are available, we propose to randomly switch between then each K generations (e.g. K=20). This new approach is tested on a ball collecting task. Results show that better fitness values are obtained with the random switch approach than with any single measure. In effect, the present contribution show that it is possible use behavioral diversity while avoiding to choose between behavioral similarity measures.

关键词： evolutionary Algorithm evolutionary robotics Neuro-Evolution Behavior Exploration Diversity Novelty

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Impact of Neuron Models and Network Structure on Evolving Modular Robot Neural Network Controllers 12

Impact of Neuron Models and Network Structure on Evolving Mo...

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14th International Conference on Genetic and evolutionary Computation Conference (GECCO)

作者： Cazenille, Leo Bredeche, Nicolas Hamann, Heiko Stradner, Juergen Univ Paris 11 CNRS INRIA TAO LRI F-91405 Orsay France

ISBN: (纸本)9781450311779

This paper investigates the properties required to evolve Artificial Neural Networks for distributed control in modular robotics, which typically involves non-linear dynamics and complex interactions in the sensori-motor space. We investigate the relation between macro-scale properties (such as modularity and regularity) and micro-scale properties in Neural Network controllers. We show how neurons capable of multiplicative-like arithmetic operations may increase the performance of controllers in several ways whenever challenging control problems with non-linear dynamics are involved. This paper provides evidence that performance and robustness of evolved controllers can be improved by a combination of carefully chosen micro- and macro-scale neural network properties.

关键词： evolutionary robotics Artificial Neural Networks evolutionary Algorithms Modular robotics

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Emergence of Memory in Neuroevolution: Impact of Selection Pressures 12

Emergence of Memory in Neuroevolution: Impact of Selection P...

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14th International Conference on Genetic and evolutionary Computation Conference (GECCO)

作者： Ollion, Charles Pinville, Tony Doncieux, Stephane Univ Pierre & Marie Curie Paris 6 ISIR CNRS UMR 7222 4 Pl Jussieu F-75252 Paris 05 France

ISBN: (纸本)9781450311786

How to drive a learning process towards the emergence of a memory? It is hypothesized here that a reward function which evaluates the fulfillment of a task requiring memory does not necessarily reward the stepping stones to this cognitive ability. This question is studied from an evolutionary robotics perspective. Both structure and parameters of a neural network supposed to exhibit a memory are generated through an evolutionary search. Results show that selective pressures driving the evolutionary search are of critical importance. We further hypothesize that one feature of controllers with a memory is their ability to exhibit consistent behaviors over different contexts. To validate this hypothesis, a new fitness objective rewarding behavior consistency in different contexts is introduced and tested on a T-maze ER task - a task involving both navigation and working memory. The efficiency of the fitness objective is studied, as well as its effects on the overall performance and generalization ability of the controller. Results show that it is complementary to a behavioral diversity objective, thus leading to improved results when using both selection pressures.

关键词： evolutionary Algorithm evolutionary robotics Neuroevolution Selection pressure

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