0000000000852019

AUTHOR

Stefano Nolfi

showing 3 related works from this author

On the coupling between agent internal and agent/ environmental dynamics: Development of spatial representations in evolving autonomous robots

2008

In this article we describe how a population of evolving robots can autonomously develop forms of spatial representation which allow them to self-localize and to discriminate different locations of their environment by integrating sensory-motor information over time. The evolving robots also display a remarkable ability to generalize their skill in new environmental conditions that they have never experienced before. The analysis of the obtained results indicates that the evolved robots come up with simple and robust solutions that exploit quasi-periodic limit cycle dynamics emerging from the coupling between the robot/environmental dynamics and a robot's internal dynamics. More specifical…

Transient dynamiceducation.field_of_studyExploitComputer scienceEvolutionDistributed computingPopulationExperimental and Cognitive Psychologydynamical systemsComputer Science::RoboticsBehavioral Neurosciencerobot navigationCoupling (computer programming)Simple (abstract algebra)Limit cycleAttractorRobotTransient (computer programming)educationadaptive behaviorSimulationSpatial representation
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Breedbot: An Edutainment Robotics System to Link Digital and Real World

2007

The paper describes Breedbot an edutainment software and hardware system that could be used to evolve autonomous agents in digital (software) world and to transfer the evolved minds in physical agents (robots). The system is based on a wide variety of Artificial Life techniques (Artificial Neural Networks, Genetic Algorithms, User Guided Evolutionary Design and Evolutionary Robotics). An user without any computer programming skill can determine the robot behaviour. Breedbot was used as a didactic tool in teaching Evolutionary Biology and as a futuristic toy by several Science Centers. The digital side of Breedbot is downloadable from www.isl.unina.it/breedbot.

business.industryComputer scienceComputer programmingAutonomous agentEvolutionary roboticsRoboticsSoftwareEvolutionary acquisition of neural topologiesHuman–computer interactionArtificial lifeGenetic algorithmRobotArtificial intelligencebusiness
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Panel Summary Perceptual Learning and Discovering

1994

The problem of learning and discovering in perception is addressed and discussed with particular reference to present machine learning paradigms. These paradigms are briefly introduced by S. Gaglio. The subsymbolic approach is addressed by S. Nolfi, and the role of symbolic learning is analysed by F. Esposito. Many of the open problems, that are evidentiated in the course of the panel, show how this is an important field of research that still needs a lot of investigation. In particular, as a result of the whole discussion, it seems that a suitable integration of different approaches must be accurately investigated. It is observed, in fact, that the weakness of the most part of the existing…

Cognitive scienceIdeal (set theory)Computer sciencebusiness.industrymedia_common.quotation_subjectNovelty detectionField (computer science)Symbolic learningPerceptual learningPerceptionIncremental learningUnsupervised learningArtificial intelligencebusinessmedia_common
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