Motivated by social insects, the possibility of evolving distributed control for a task requiring global coordination is investigated. The task is object clustering. A key aspect of this work is that a population of robot-like agents is allowed to select the cluster location.
The task is object clustering. A key aspect of this work is that a population of robot-like agents is allowed to select the cluster location.
The task is object clustering. A key aspect of this work is that a population of robot-like agents is allowed to select the cluster location.
Evolving Distributed Control for an Object Clustering Task
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A detailed examination of how solutions evolved by a genetic algorithm are able to scale as key parameters are varied is presented, allowing commentary on the ...
Volume 15, Issue 3 (2005). Evolving Distributed Control for an Object Clustering Task · Download PDF. Timothy D. Barfoot Gabriele M. T. D'Eleuterio ...
Timothy D. Barfoot, Gabriele M. T. D'Eleuterio: Evolving Distributed Control for an Object Clustering Task. Complex Syst. 15(3) (2005). manage site settings.
Learning Distributed Control for an Object-Clustering Task
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This paper proposes an evolutionary multi-objective optimization approach for load frequency control in interconnected power systems. The design purpose is to ...
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This paper reports on experiments involving a hexapod robot. Motivated by neurobiological evidence that control in real hexapod insects is distributed ...
Nov 26, 2021 · This paper presents a teaching-learning-based optimization algorithm for discrete large-scale multi-objective problems (DLM-TLBO).
Online clustering can be applied to single tasks as well as to complex systems where data come over time in a continuous stream.