Automated negotiations under user preference uncertainty: A linear programming approach

Dimitrios Tsimpoukis, Tim Baarslag, Michael Kaisers, Nikolaos G. Paterakis

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)
1 Downloads (Pure)


Autonomous agents negotiating on our behalf find applications in everyday life in many domains such as high frequency trading, cloud computing and the smart grid among others. The agents negotiate with one another to reach the best agreement for the users they represent. An obstacle in the future of automated negotiators is that the agent may not always have a priori information about the preferences of the user it represents. The purpose of this work is to develop an agent that will be able to negotiate given partial information about the user’s preferences. First, we present a new partial information model that is supplied to the agent, which is based on categorical data in the form of pairwise comparisons of outcomes instead of precise utility information. Using this partial information, we develop an estimation model that uses linear optimization and translates the information into utility estimates. We test our methods in a negotiation scenario based on a smart grid cooperative where agents participate in energy trade-offs. The results show that already with very limited information the model becomes accurate quickly and performs well in an actual negotiation setting. Our work provides valuable insight into how uncertainty affects an agent’s negotiation performance, how much information is needed to be able to formulate an accurate user model, and shows a capability of negotiating effectively with minimal user feedback.

Original languageEnglish
Title of host publicationAgreement Technologies - 6th International Conference, AT 2018, Revised Selected Papers
EditorsMarin Lujak
Place of PublicationCham
Number of pages15
ISBN (Print)9783030172930
Publication statusPublished - 4 Apr 2019
Event6th International Conference on Agreement Technologies, (AT2018) - Bergen, Norway
Duration: 6 Dec 20187 Dec 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11327 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference6th International Conference on Agreement Technologies, (AT2018)
Abbreviated titleAT2018
Internet address


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