Compromising Adjustment Strategy Based on TKI Conflict Mode for Multi‐Times Bilateral Closed Negotiations

Compromising Adjustment Strategy Based on TKI Conflict Mode for Multi‐Times Bilateral Closed... Bilateral multi‐issue closed negotiation is an important class for real‐life negotiations. Usually, negotiation problems have constraints such as a complex and unknown opponent's utility in real time, or time discounting. In the class of negotiation with some constraints, the effective automated negotiation agents can adjust their behavior depending on the characteristics of their opponents and negotiation scenarios. Recently, the attention of this study has focused on the interleaving learning with negotiation strategies from the past negotiation sessions. By analyzing the past negotiation sessions, agents can estimate the opponent's utility function based on exchanging bids. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computational Intelligence Wiley

Compromising Adjustment Strategy Based on TKI Conflict Mode for Multi‐Times Bilateral Closed Negotiations

Loading next page...
 
/lp/wiley/compromising-adjustment-strategy-based-on-tki-conflict-mode-for-multi-h9cGp0AvlQ
Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
© 2018 Wiley Periodicals, Inc.
ISSN
0824-7935
eISSN
1467-8640
D.O.I.
10.1111/coin.12107
Publisher site
See Article on Publisher Site

Abstract

Bilateral multi‐issue closed negotiation is an important class for real‐life negotiations. Usually, negotiation problems have constraints such as a complex and unknown opponent's utility in real time, or time discounting. In the class of negotiation with some constraints, the effective automated negotiation agents can adjust their behavior depending on the characteristics of their opponents and negotiation scenarios. Recently, the attention of this study has focused on the interleaving learning with negotiation strategies from the past negotiation sessions. By analyzing the past negotiation sessions, agents can estimate the opponent's utility function based on exchanging bids.

Journal

Computational IntelligenceWiley

Published: Jan 1, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off