IEICE TRANSACTIONS on Information
Meta-Strategy Based on Multi-Armed Bandit Approach for Multi-Time Negotiation
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Information Vol.E103-D No.12 pp.2540-2548
- Publication Date
- 2020/12/01
- Publicized
- 2020/09/07
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2020SAP0003
- Type of Manuscript
- Special Section PAPER (Special Section on Software Agent and Its Applications)
- Category
Authors
Ryohei KAWATA
Tokyo University of Agriculture and Technology
Katsuhide FUJITA
Tokyo University of Agriculture and Technology
Keyword
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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
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@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},}
Copy
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 -
English
