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
Y1 - 2010
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
T3 - Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10
SP - 1311
EP - 1312
BT - Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10
T2 - 12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010
Y2 - 7 July 2010 through 11 July 2010
ER -