Distributed task selection in multi-agent based swarms using heuristic strategies

David Miller, Prithviraj Dasgupta, Timothy Judkins

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Swarm-based systems have emerged as an attractive paradigm for implementing distributed autonomous systems for various applications in commercial, military and business domains. One of the major operations in a swarm-based system is to ensure that the individual swarm units process the tasks in the environment in an efficient manner. This can be achieved using a suitable task selection mechanism that allocates the desired number of swarm units to each task while reducing inter-task latencies and communication overhead, and, ensuring adequate commitment of resources to tasks. In this paper, we describe a multi-agent based distributed task selection mechanism for swarm-based systems. We show that the distributed task selection problem is NP-complete and propose polynomial-time heuristic-based algorithms. Our simulation results show that heuristics in which each swarm unit considers both the effects of other swarm units on tasks and its own relative position to other swarm units achieve better task processing efficiency and improved distribution of swarm units over tasks.

Original languageEnglish (US)
Title of host publicationSwarm Robotics - 2nd International Workshop, SAB 2006
Pages158-173
Number of pages16
StatePublished - Dec 1 2007
Event2nd International Workshop on Swarm Robotics, SAB 2006 - Rome, Italy
Duration: Sep 30 2006Oct 1 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4433 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Workshop on Swarm Robotics, SAB 2006
CountryItaly
CityRome
Period9/30/0610/1/06

Fingerprint

Swarm
Chemical reactions
Computational complexity
Polynomials
Heuristics
Computer Communication Networks
Communication
Processing
Industry
Unit
Efficiency
Strategy
Autonomous Systems
Military
Latency
Distributed Systems
Polynomial time
NP-complete problem
Paradigm
Resources

Keywords

  • Heuristics
  • Multi-agent swarming
  • Task allocation
  • Webots

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Miller, D., Dasgupta, P., & Judkins, T. (2007). Distributed task selection in multi-agent based swarms using heuristic strategies. In Swarm Robotics - 2nd International Workshop, SAB 2006 (pp. 158-173). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4433 LNCS).

Distributed task selection in multi-agent based swarms using heuristic strategies. / Miller, David; Dasgupta, Prithviraj; Judkins, Timothy.

Swarm Robotics - 2nd International Workshop, SAB 2006. 2007. p. 158-173 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4433 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Miller, D, Dasgupta, P & Judkins, T 2007, Distributed task selection in multi-agent based swarms using heuristic strategies. in Swarm Robotics - 2nd International Workshop, SAB 2006. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4433 LNCS, pp. 158-173, 2nd International Workshop on Swarm Robotics, SAB 2006, Rome, Italy, 9/30/06.
Miller D, Dasgupta P, Judkins T. Distributed task selection in multi-agent based swarms using heuristic strategies. In Swarm Robotics - 2nd International Workshop, SAB 2006. 2007. p. 158-173. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Miller, David ; Dasgupta, Prithviraj ; Judkins, Timothy. / Distributed task selection in multi-agent based swarms using heuristic strategies. Swarm Robotics - 2nd International Workshop, SAB 2006. 2007. pp. 158-173 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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