Automatic creation of an autonomous agent: genetic evolution of a neural-network driven robot
Dario Floreano,Francesco Mondada +1 more
- pp 421-430
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The paper describes the results of the evolutionary development of a real, neural-network driven mobile robot, and shows a number of emergent phenomena that are characteristic of autonomous agents.Abstract:
The paper describes the results of the evolutionary development of a real, neural-network driven mobile robot. The evolutionary approach to the development of neural controllers for autonomous agents has been successfully used by many researchers, but most - if not all - studies have been carried out with computer simulations. Instead, in this research the whole evolutionary process takes places entirely on a real robot without human intervention. Although the experiments described here tackle a simple task of navigation and obstacle avoidance, we show a number of emergent phenomena that are characteristic of autonomous agents. The neural controllers of the evolved best individuals display a full exploitation of non-linear and recurrent connections that make them more efficient than analogous man-designed agents. In order to fully understand and describe the robot behavior, we have also employed quantitative ethological tools [13], and showed that the adaptation dynamics conform to predictions made for animals.read more
Citations
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The Nature of Life: Classical and Contemporary Perspectives from Philosophy and Science: Preface
Mark Bedau,OregonCarol Cleland +1 more
Proceedings ArticleDOI
Evolutionary robotics: exploiting the full power of self-organization
TL;DR: Although the authors think that evolutionary robotics may be relevant for many different fields, they restrict their analysis to engineering, biology, and ethology.
Book ChapterDOI
Hardware Solutions for Evolutionary Robotics
Dario Floreano,Francesco Mondada +1 more
TL;DR: This work outlines a set of hardware solutions and working methodologies that can be used for successfully implementing and extending the evolutionary approach to complex environments, robots, and real-world applications.
Journal Article
Learning complex robot behaviours by evolutionary computing with task decomposition
TL;DR: This work analyses the difficulties of applying evolutionary approaches to learn complex behaviours for mobile robots and proposes to take the control architecture of a behavior-based system and to learn the separate behaviours and the arbitration by the use of an evolutionary approach.
Journal ArticleDOI
Evolutionary design and behavior analysis of neuromodulatory neural networks for mobile robots control
TL;DR: The author focused on evolving an on-line learning ability instead of weight parameters in a simulated environment and a neuromodulatory neural network model was proposed and it was utilized as a mobile robot controller.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Intelligence without Representation
TL;DR: Brooks et al. as mentioned in this paper decompose an intelligent system into independent and parallel activity producers which all interface directly to the world through perception and action, rather than interface to each other particularly much.
Journal ArticleDOI
Intelligence without representation
TL;DR: Brooks et al. as discussed by the authors decompose an intelligent system into independent and parallel activity producers which all interface directly to the world through perception and action, rather than interface to each other particularly much.