Human-Agent Negotiations: The Impact Agents' Concession Schedule and Task Complexity on Agreements

Employment of software agents for conducting negotiations with online customers promises to increase the flexibility and reach of the exchange mechanism and reduce transaction costs. Past research had suggested different negotiation tactics for the agents, and had used them in experimental settings against human negotiators. This work explores the interaction between negotiation strategies and the complexity of the negotiation task as represented by the number of negotiation issues. Including more issues in a negotiation potentially allows the parties more space to maneuver and, thus, promises higher likelihood of agreement. In practice, the consideration of more is-sues requires higher cognitive effort, which could have a negative effect on reaching an agreement. The results of human– agent negotiation experiments conducted at a major Canadian university revealed that there is an interaction between chosen strategy and task complexity. Also, when competitive strategy was employed, the agents' utility was the highest. Because competitive strategy resulted in fewer agreements the average utility per agent was the highest in the compromising–competitive strategy.

[1]  Gregory Kersten,et al.  Experimental Assessment of Agent-Supported Electronic Negotiations , 2013, Int. J. Hum. Comput. Interact..

[2]  D. Baca,et al.  A cognitive approach to language learning , 2006 .

[3]  Fu-Ren Lin,et al.  The design and evaluation of an intelligent sales agent for online persuasion and negotiation , 2007, Electron. Commer. Res. Appl..

[4]  Gregory E. Kersten,et al.  Negotiation via the World Wide Web: A Cross-cultural Study of Decision Making , 1999 .

[5]  Gregory E. Kersten,et al.  An experimental study of software agent negotiations with humans , 2014, Decis. Support Syst..

[6]  C. D. De Dreu,et al.  Task versus relationship conflict, team performance, and team member satisfaction: a meta-analysis. , 2003, The Journal of applied psychology.

[7]  Michael J. Prietula,et al.  Getting to best: efficiency versus optimality in negotiation , 2000, Cogn. Sci..

[8]  Andreas Fink,et al.  Learning from the Metaheuristics: Protocols for Automated Negotiations , 2015 .

[9]  Bo Yu,et al.  Effects of negotiation tactics and task complexity in software agent: human negotiations , 2016, ICEC.

[10]  Michael J. Prietula,et al.  Negotiation Offers and the Search for Agreement , 2011 .

[11]  Pattie Maes,et al.  Kasbah: An Agent Marketplace for Buying and Selling Goods , 1996, PAAM.

[12]  Jeffrey M. Bradshaw,et al.  Ten Challenges for Making Automation a "Team Player" in Joint Human-Agent Activity , 2004, IEEE Intell. Syst..

[13]  L. Thompson,et al.  The Mind and Heart of the Negotiator , 1997 .

[14]  Andrea Kupfer Schneider,et al.  Reputations in Negotiation , 2008 .

[15]  Gregory E. Kersten,et al.  Aspire: an integrated negotiation support system and software agents for e-business negotiation , 2003, Int. J. Internet Enterp. Manag..

[16]  P. Dillenbourg,et al.  NEGOTIATION SPACES IN HUMAN-COMPUTER COLLABORATIVE LEARNING , 1996 .

[17]  Jacques L. Koko,et al.  The Art and Science of Negotiation , 2009 .

[18]  Takayuki Ito,et al.  Next Frontier in Agent-Based Complex Automated Negotiation , 2015, Next Frontier in Agent-Based Complex Automated Negotiation.

[19]  R. Bennett,et al.  The impact of consideration of issues and motivational orientation on group negotiation process and outcome. , 1993 .

[20]  Sarit Kraus,et al.  Can automated agents proficiently negotiate with humans? , 2010, CACM.

[21]  Nicholas R. Jennings,et al.  Guest Editors' Introduction: Agents and Markets , 2003, IEEE Intell. Syst..

[22]  Nicholas R. Jennings,et al.  Negotiation decision functions for autonomous agents , 1998, Robotics Auton. Syst..

[23]  Robert H. Guttman,et al.  Cooperative vs. Competitive Multi-Agent Negotiations in Retail Electronic Commerce , 1998, CIA.

[24]  Charles B. Craver,et al.  Effective legal negotiation and settlement , 1986 .

[25]  Jonathan Gratch,et al.  The effect of expression of anger and happiness in computer agents on negotiations with humans , 2011, AAMAS.

[26]  Pattie Maes,et al.  Agents that buy and sell , 1999, CACM.

[27]  Yunjie Calvin Xu,et al.  Offer with Choices and Accept with Delay: A Win-Win Strategy Model for Agent Based Automated Negotiation , 2009, ICIS.

[28]  Robert W. Blanning,et al.  Decision Support Systems and Internet Commerce , 2000, Handbook of Electronic Commerce.

[29]  I. Benbasat,et al.  The Effects of Group, Task,Context, and Technology Variables on the Usefulness of Group Support Systems , 1993 .

[30]  Jeffrey S. Rosenschein and Gilad Zlotkin Rules of Encounter , 1994 .

[31]  Gregory E. Kersten,et al.  Agent-supported negotiations in the e-marketplace , 2005, Int. J. Electron. Bus..

[32]  Bo Yu,et al.  Agents and E-commerce: Beyond Automation , 2015, AMCIS.

[33]  Nicholas R. Jennings,et al.  An agenda-based framework for multi-issue negotiation , 2004, Artif. Intell..

[34]  Sarit Kraus,et al.  DESIGNING AND BUILDING A NEGOTIATING AUTOMATED AGENT , 1995, Comput. Intell..

[35]  Katia Sycara,et al.  Multiagent Compromise via Negotiation , 1989, Distributed Artificial Intelligence.

[36]  Russell B. Korobkin,et al.  Heuristics and Biases at the Bargaining Table , 2004 .

[37]  Pattie Maes,et al.  A Real-Life Experiment in Creating an Agent Marketplace , 1997, Software Agents and Soft Computing.

[38]  Claudio Bartolini,et al.  AutONA: a system for automated multiple 1-1 negotiation , 2003, EEE International Conference on E-Commerce, 2003. CEC 2003..