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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Book ChapterDOI
Evolutionary Computation of Multi-robot/agent Systems
TL;DR: The last (but not least) common point between evolutionary computation and multiagent systems is the similarity between emergence and evolution; previous works have shown that a population is able to perform tasks that an isolated agent is not able to do.
Book ChapterDOI
Polymorphy and Hybridization in Genetically Programmed Networks
TL;DR: The polymorphic abilities of a new distributed representation for genetic programming, called Genetically Programmed Networks, are discussed, which allows the fast exploration of various search spaces thus increasing the possibility of finding a (or a better) solution.
Proceedings ArticleDOI
Evolutionary design of autonomous agent based on gate growth
K. Takita,Y. Kakazu +1 more
TL;DR: A new approach "gate growth", which is a grammar encoding network construction method, is presented, which consists of a cellular automaton as a connection algorithm and an NAND array as a device model that are evolved to achieve given tasks.
Book ChapterDOI
Data Communication Assistance via Swarm Robotic: A Behaviour Creation Comparison
TL;DR: This paper compares two behaviour creation algorithms for Unmanned Aerial Vehicle swarms to have a self-organising robotic swarm which unintrusively assists humans in network restricted environments by facilitating data-transfer between disconnected groups.
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.