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Learning and adaptation in physical heterogeneous teams of robots

In this paper we present a novel approach to assigning roles to robots in a team of physical heterogeneous robots. Its members compete for these roles and get rewards for them. The rewards are used to determine each agent’s preferences and which agents are better adapted to the environment. These aspects are included in the decision making process. Agent interactions are modelled using the concept of an ecosystem in which each robot is a species, resulting in emergent behaviour of the whole set of agents. One of the most important features of this approach is its high adaptability. Unlike some other learning techniques, this approach does not need to start a whole exploitation process when the environment changes. All this is exemplified by means of experiments run on a simulator. In addition, the algorithm developed was applied as applied to several teams of robots in order to analyse the impact of heterogeneity in these systems

Red de Agentes Físicos

Author: Rosa, Josep Lluís de la
Muñoz Moreno, Israel
Abstract: In this paper we present a novel approach to assigning roles to robots in a team of physical heterogeneous robots. Its members compete for these roles and get rewards for them. The rewards are used to determine each agent’s preferences and which agents are better adapted to the environment. These aspects are included in the decision making process. Agent interactions are modelled using the concept of an ecosystem in which each robot is a species, resulting in emergent behaviour of the whole set of agents. One of the most important features of this approach is its high adaptability. Unlike some other learning techniques, this approach does not need to start a whole exploitation process when the environment changes. All this is exemplified by means of experiments run on a simulator. In addition, the algorithm developed was applied as applied to several teams of robots in order to analyse the impact of heterogeneity in these systems
Document access: http://hdl.handle.net/2072/42646
Language: eng
Publisher: Red de Agentes Físicos
Rights: Reconeixement-CompartirIgual 3.0 Espanya
Rights URI: http://creativecommons.org/licenses/by-sa/3.0/es/deed.ca
Subject: Control intel·ligent
Robots
Intelligent control systems
Title: Learning and adaptation in physical heterogeneous teams of robots
Type: info:eu-repo/semantics/article
Repository: Recercat

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