The aim of this paper is to study the emergenceof coordinated activities, and the investigation of collaboration between individuals in a small group of robots. The idea is to impose very simple global rules and to give a primary role to the environment mediation. In the paper the specialization strategy, already introduced in a previous work is extended, to autonomously solve a task assignment problem among agents in an initially homogeneous swarm. In particular, a givensequence of tasks is assigned to the group and each robot has to autonomously specialise in solving sub-sequences, resulting in a labor division which improves the performance of the team. Behavioral improvement is guided by a global reward function. Results, obtained in a dynamic simulation environment, show that performances depend by environmental conditions andstarting positions of the singular agents: environment and the other robots play clearly a fundamental role in mediating the swarm capabilities.

Autonomous Learning of collaboration among robots

ARENA, Paolo Pietro;Patané L;VITANZA, ALESSANDRA
2012-01-01

Abstract

The aim of this paper is to study the emergenceof coordinated activities, and the investigation of collaboration between individuals in a small group of robots. The idea is to impose very simple global rules and to give a primary role to the environment mediation. In the paper the specialization strategy, already introduced in a previous work is extended, to autonomously solve a task assignment problem among agents in an initially homogeneous swarm. In particular, a givensequence of tasks is assigned to the group and each robot has to autonomously specialise in solving sub-sequences, resulting in a labor division which improves the performance of the team. Behavioral improvement is guided by a global reward function. Results, obtained in a dynamic simulation environment, show that performances depend by environmental conditions andstarting positions of the singular agents: environment and the other robots play clearly a fundamental role in mediating the swarm capabilities.
978-1-4673-1488-6
Forward models; Moving platform; Bio-inspired Control architecture,
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/84945
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