Abstract
In this paper, we introduce the probabilistic awardee selection strategy, under which awardee is selected with a fixed probability, into the award phase of contract net protocol. We then point out that, by changing the probabilities in this strategy according the local workload, the overall performance can be considerably improved.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10 |
| Pages | 1311-1312 |
| Number of pages | 2 |
| DOIs | |
| Publication status | Published - 2010 Aug 27 |
| Externally published | Yes |
| Event | 12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010 - Portland, OR, United States Duration: 2010 Jul 7 → 2010 Jul 11 |
Other
| Other | 12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010 |
|---|---|
| Country | United States |
| City | Portland, OR |
| Period | 10/7/7 → 10/7/11 |
Fingerprint
Keywords
- Adaptive behavior
- Contract net protocol
- Distributed task allocation
- Load-balancing
- Optimization
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Theoretical Computer Science
Cite this
Adaptive probabilistic task allocation in large-scale multi-agent systems and its evaluation. / Sugawara, Toshiharu; Fukuda, Kensuke; Hirotsu, Toshio; Kurihara, Satoshi.
Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10. 2010. p. 1311-1312.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Adaptive probabilistic task allocation in large-scale multi-agent systems and its evaluation
AU - Sugawara, Toshiharu
AU - Fukuda, Kensuke
AU - Hirotsu, Toshio
AU - Kurihara, Satoshi
PY - 2010/8/27
Y1 - 2010/8/27
N2 - In this paper, we introduce the probabilistic awardee selection strategy, under which awardee is selected with a fixed probability, into the award phase of contract net protocol. We then point out that, by changing the probabilities in this strategy according the local workload, the overall performance can be considerably improved.
AB - In this paper, we introduce the probabilistic awardee selection strategy, under which awardee is selected with a fixed probability, into the award phase of contract net protocol. We then point out that, by changing the probabilities in this strategy according the local workload, the overall performance can be considerably improved.
KW - Adaptive behavior
KW - Contract net protocol
KW - Distributed task allocation
KW - Load-balancing
KW - Optimization
UR - http://www.scopus.com/inward/record.url?scp=77955855611&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77955855611&partnerID=8YFLogxK
U2 - 10.1145/1830483.1830718
DO - 10.1145/1830483.1830718
M3 - Conference contribution
AN - SCOPUS:77955855611
SN - 9781450300728
SP - 1311
EP - 1312
BT - Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10
ER -