The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Rundingan berbilang masa yang mengulangi rundingan berkali-kali dalam keadaan yang sama ialah kelas rundingan automatik yang penting. Kami mencadangkan strategi meta yang memilih strategi rundingan individu ejen untuk rundingan berbilang masa. Oleh kerana prestasi ejen perundingan bergantung pada parameter situasi, seperti domain perundingan dan pihak lawan, strategi individu yang sesuai dan berkesan harus dipilih mengikut situasi perundingan. Walau bagaimanapun, kebanyakan ejen sedia ada berunding berdasarkan hanya satu dasar perundingan: satu strategi pembidaan, satu strategi penerimaan dan satu kaedah pemodelan lawan. Walaupun ejen sedia ada berunding dengan berkesan dalam kebanyakan situasi, mereka tidak berfungsi dengan baik dalam situasi tertentu dan utiliti mereka berkurangan. Strategi meta yang dicadangkan menyediakan strategi rundingan yang berkesan untuk situasi pada permulaan rundingan. Kami memodelkan strategi meta sebagai masalah penyamun berbilang senjata yang menganggap strategi rundingan individu sebagai mesin slot dan utiliti ejen sebagai ganjaran. Kami melaksanakan strategi meta sebagai ejen perundingan yang menggunakan ejen berkesan sedia ada sebagai strategi individu. Keputusan eksperimen menunjukkan keberkesanan meta-strategi kami di bawah pelbagai keadaan rundingan. Selain itu, keputusan menunjukkan bahawa utiliti individu ejen perundingan dipengaruhi oleh strategi pihak lawan, profil pihak lawan dan profilnya sendiri.
Ryohei KAWATA
Tokyo University of Agriculture and Technology
Katsuhide FUJITA
Tokyo University of Agriculture and Technology
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Salinan
Ryohei KAWATA, Katsuhide FUJITA, "Meta-Strategy Based on Multi-Armed Bandit Approach for Multi-Time Negotiation" in IEICE TRANSACTIONS on Information,
vol. E103-D, no. 12, pp. 2540-2548, December 2020, doi: 10.1587/transinf.2020SAP0003.
Abstract: Multi-time negotiation which repeats negotiations many times under the same conditions is an important class of automated negotiation. We propose a meta-strategy that selects an agent's individual negotiation strategy for multi-time negotiation. Because the performance of the negotiating agents depends on situational parameters, such as the negotiation domains and the opponents, a suitable and effective individual strategy should be selected according to the negotiation situation. However, most existing agents negotiate based on only one negotiation policy: one bidding strategy, one acceptance strategy, and one opponent modeling method. Although the existing agents effectively negotiate in most situations, they do not work well in particular situations and their utilities are decreased. The proposed meta-strategy provides an effective negotiation strategy for the situation at the beginning of the negotiation. We model the meta-strategy as a multi-armed bandit problem that regards an individual negotiation strategy as a slot machine and utility of the agent as a reward. We implement the meta-strategy as the negotiating agents that use existing effective agents as the individual strategies. The experimental results demonstrate the effectiveness of our meta-strategy under various negotiation conditions. Additionally, the results indicate that the individual utilities of negotiating agents are influenced by the opponents' strategies, the profiles of the opponent and its own profiles.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2020SAP0003/_p
Salinan
@ARTICLE{e103-d_12_2540,
author={Ryohei KAWATA, Katsuhide FUJITA, },
journal={IEICE TRANSACTIONS on Information},
title={Meta-Strategy Based on Multi-Armed Bandit Approach for Multi-Time Negotiation},
year={2020},
volume={E103-D},
number={12},
pages={2540-2548},
abstract={Multi-time negotiation which repeats negotiations many times under the same conditions is an important class of automated negotiation. We propose a meta-strategy that selects an agent's individual negotiation strategy for multi-time negotiation. Because the performance of the negotiating agents depends on situational parameters, such as the negotiation domains and the opponents, a suitable and effective individual strategy should be selected according to the negotiation situation. However, most existing agents negotiate based on only one negotiation policy: one bidding strategy, one acceptance strategy, and one opponent modeling method. Although the existing agents effectively negotiate in most situations, they do not work well in particular situations and their utilities are decreased. The proposed meta-strategy provides an effective negotiation strategy for the situation at the beginning of the negotiation. We model the meta-strategy as a multi-armed bandit problem that regards an individual negotiation strategy as a slot machine and utility of the agent as a reward. We implement the meta-strategy as the negotiating agents that use existing effective agents as the individual strategies. The experimental results demonstrate the effectiveness of our meta-strategy under various negotiation conditions. Additionally, the results indicate that the individual utilities of negotiating agents are influenced by the opponents' strategies, the profiles of the opponent and its own profiles.},
keywords={},
doi={10.1587/transinf.2020SAP0003},
ISSN={1745-1361},
month={December},}
Salinan
TY - JOUR
TI - Meta-Strategy Based on Multi-Armed Bandit Approach for Multi-Time Negotiation
T2 - IEICE TRANSACTIONS on Information
SP - 2540
EP - 2548
AU - Ryohei KAWATA
AU - Katsuhide FUJITA
PY - 2020
DO - 10.1587/transinf.2020SAP0003
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E103-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2020
AB - Multi-time negotiation which repeats negotiations many times under the same conditions is an important class of automated negotiation. We propose a meta-strategy that selects an agent's individual negotiation strategy for multi-time negotiation. Because the performance of the negotiating agents depends on situational parameters, such as the negotiation domains and the opponents, a suitable and effective individual strategy should be selected according to the negotiation situation. However, most existing agents negotiate based on only one negotiation policy: one bidding strategy, one acceptance strategy, and one opponent modeling method. Although the existing agents effectively negotiate in most situations, they do not work well in particular situations and their utilities are decreased. The proposed meta-strategy provides an effective negotiation strategy for the situation at the beginning of the negotiation. We model the meta-strategy as a multi-armed bandit problem that regards an individual negotiation strategy as a slot machine and utility of the agent as a reward. We implement the meta-strategy as the negotiating agents that use existing effective agents as the individual strategies. The experimental results demonstrate the effectiveness of our meta-strategy under various negotiation conditions. Additionally, the results indicate that the individual utilities of negotiating agents are influenced by the opponents' strategies, the profiles of the opponent and its own profiles.
ER -