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Reinforcement Learning on Robot Swarms

Grant number: 12/14820-7
Support type:Scholarships in Brazil - Master
Effective date (Start): March 01, 2013
Effective date (End): March 31, 2014
Field of knowledge:Physical Sciences and Mathematics - Computer Science
Principal researcher:Roseli Aparecida Francelin Romero
Grantee:Murillo Rehder Batista
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

In this project, the use of a reinforcement learning through an hierarchical neural network is proposed to manage behaviors of a robot swarm in order to enhance their collective actions to execute tasks. The chosen reinforcement model is able to balance the influence of previously implemented behaviors through interaction with the environment. Each robot has its own neural network, acquiring its knowledge individually through this interaction and also by sharing information with neighboring robots. In order do evaluate effectiveness, an escorting task is given to be done balancing two behaviors: area coverage through Centroidal Voronoi Tesselations and mainentance of a distance between a robot and a given target. To test the proposed approach, escort scenarios will be simulated in the Player/Stage environment.

Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
BATISTA, Murillo Rehder. Hierarchical neural network for online robot swarm learning. 2014. Master's Dissertation - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação São Carlos.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.