TY  - GEN
ID  - cogprints2521
UR  - http://cogprints.org/2521/
A1  - Nehmzow, Ulrich
Y1  - 2002///
N2  - We present experiments in which a group of autonomous mobile robots learn to perform fundamental sensor-motor tasks through a collaborative learning process. Behavioural strategies, i.e. motor responses to sensory stimuli, are encoded by means of genetic strings stored on the individual robots, and adapted through a genetic algorithm (Mitchell, 1998) executed by the entire robot collective: robots communicate their own strings and corresponding fitness to each other, and then execute a genetic algorithm to improve their individual behavioural strategy.
The robots acquired three different sensormotor competences, as well as the ability to select one of two, or one of three behaviours depending on context ("behaviour management"). Results show that fitness indeed increases with increasing learning time, and the analysis of the acquired behavioural strategies demonstrates that they are effective in accomplishing the desired task.
PB  - Lund University Cognitive Studies
KW  - mobile robots
KW  -  collaborative learning
KW  -  genetic algorithm
KW  -  PEGA
TI  - Physically Embedded Genetic Algorithm Learning in Multi-Robot Scenarios: The PEGA algorithm
SP  - 115
AV  - public
EP  - 123
ER  -

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