Tactical task allocation and resource management in non-stationary swarm dynamics

Author

Roach, Jon H. ; Marks, Robert J. ; Thompson, Benjamin B.

Author_Institution

L3 Mission Integration, Greenville, TX, USA

fYear

2013

fDate

4-9 Aug. 2013

Firstpage

1

Lastpage

5

Abstract

The allocation of resources between tasks within a swarm of agents can be difficult without a centralized controller. Disjunctive control has been shown to be a viable method to control the behavior of a swarm. In this project, a disjunctive fuzzy control system is used to solve the problem of resource management. A multi-state swarm is evolved with an offline learning algorithm to adapt to a dynamic scenario with multiple objectives. Some of the emergent behaviors developed through the evolutionary algorithm were state-switching and recruitment techniques.

Keywords

centralised control; evolutionary computation; fuzzy control; learning (artificial intelligence); multi-agent systems; centralized controller; disjunctive control; disjunctive fuzzy control system; evolutionary algorithm; multistate swarm; nonstationary swarm dynamics; offline learning algorithm; recruitment techniques; resource management; state switching techniques; swarm behavior; tactical task allocation; Educational institutions; Particle swarm optimization; Recruitment; Sensors; Sociology; Statistics; Switches; emergent behavior; fuzzy control; multi-state; swarm intelligence; task switching;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks (IJCNN), The 2013 International Joint Conference on

Conference_Location

Dallas, TX

ISSN

2161-4393

Print_ISBN

978-1-4673-6128-6

Type

conf

DOI

10.1109/IJCNN.2013.6706879

Filename

6706879