Decision making of negotiation agents using markov chains

Bo An*, Kwang Mong Sim, Chun Yan Miao, Zhi Qi Shen

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

13 Citations (Scopus)


In dynamic and complex negotiation environments, a negotiation agent can participate or quit negotiation at any time and can potentially reach an agreement with more than one trading partner as the result of the existence of dynamic outside options. Thus, it’s important for a negotiation agent to make a decision on when to complete negotiation given its trading partners’ current proposals and market dynamics. Rather than explicitly modeling all the trading partners, this paper presents a novel decision making strategy based on a tractable Markov chain model of negotiation process. An agent can use this model to determine whether to accept the best proposal of its trading partners or let negotiation proceed forward during each round of negotiation. Experimental results suggest that the proposed strategy achieved more favorable negotiation outcomes as compared with the general strategy.

Original languageEnglish
Pages (from-to)5-23
Number of pages19
JournalMultiagent and Grid Systems
Issue number1
Publication statusPublished - 8 May 2008
Externally publishedYes

Scopus Subject Areas

  • Computer Science(all)

User-Defined Keywords

  • Automated negotiation
  • Markov chains
  • Negotiation agents


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