Title
Distributed task selection in multi-agent based swarms using heuristic strategies
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.
Year
DOI
Venue
2006
10.1007/978-3-540-71541-2_11
Swarm Robotics
Keywords
Field
DocType
autonomous system,individual swarm unit,swarm unit,better task processing efficiency,heuristic strategy,attractive paradigm,swarm-based system,task selection mechanism,task selection problem,suitable task selection mechanism,adequate commitment,heuristics,polynomial time
Heuristic,Swarm behaviour,Computer science,Multi-swarm optimization,Heuristics,Autonomous system (Internet),Artificial intelligence
Conference
Volume
ISSN
Citations 
4433
0302-9743
6
PageRank 
References 
Authors
0.64
22
3
Name
Order
Citations
PageRank
David J. Miller142160.29
Prithviraj Dasgupta236358.78
Timothy Judkins360.97