Archived project

Pocket Negotiator, synergy between man and machine

Goal: To develop a new type of human-machine collaborative system that combines the strengths of human and machine and reduces their weaknesses in negotiation. Fundamental in these systems will be that user and machine explicitly share a generic task model and that such systems are to support humans in coping with emotions and moods in human-human interactions. For this purpose we will contribute new concepts, methods and techniques. For integrative bargaining we will develop such a system, called a Pocket Negotiator, to collaborate with human negotiators.

Date: 1 June 2008 - 20 May 2014

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Project log

Koen V. Hindriks
added 41 research items
In order to successfully reach an agreement in a negotiation, both parties rely on each other to make concessions. The willingness to concede also depends in large part on the opponent. A concession by the opponent may be reciprocated, but the negotiation process may also be frustrated if the opponent does not concede at all. This process of concession making is a central theme in many of the classic and current automated negotiation strategies. In this paper, we present a quantitative classification method of negotiation strategies that measures the willingness of an agent to concede against different types of opponents. The method is then applied to classify some well-known negotiating strategies, including the agents of ANAC 2010. It is shown that the technique makes it easy to identify the main characteristics of negotiation agents, and can be used to group negotiation strategies into categories with common negotiation characteristics. We also observe, among other things, that different kinds of opponents call for a different approach in making concessions.
Motivated by the challenges of bilateral negotiations between people and automated agents we organized the first automated negotiating agents competition (ANAC 2010). The purpose of the competition is to facilitate the research in the area bilateral multi-issue closed negotiation. The competition was based on the Genius environment, which is a General Environment for Negotiation with Intelligent multi-purpose Usage Simulation. The first competition was held in conjunction with the Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS-10) and was comprised of seven teams. This paper presents an overview of the competition, as well as general and contrasting approaches towards negotiation strategies that were adopted by the participants of the competition. Based on analysis in post–tournament experiments, the paper also attempts to provide some insights with regard to effective approaches towards the design of negotiation strategies.
An important aim in bilateral negotiations is to achieve a win-win solution for both parties; therefore, a critical aspect of a negotiating agent’s success is its ability to take the opponent’s preferences into account. Every year, new negotiation agents are introduced with better learning techniques to model the opponent. Our main goal in this work is to evaluate and compare the performance of a selection of state-of-the-art online opponent modeling techniques in negotiation, and to determine under which circumstances they are beneficial in a real-time, online negotiation setting. Towards this end, we provide an overview of the factors influencing the quality of a model and we analyze how the performance of opponent models depends on the negotiation setting. This results in better insight into the performance of opponent models, and allows us to pinpoint well-performing opponent modeling techniques that did not receive much previous attention in literature.
Tim Baarslag
added a research item
The Pocket Negotiator (PN) is a negotiation support system developed at TU Delft as a tool for supporting people in bilateral negotiations over multi-issue negotiation problems in arbitrary domains. Users are supported in setting their preferences, estimating those of their opponent, during the bidding phase and sealing the deal. We describe the overall architecture, the essentials of the underlying techniques, the form that support takes during the negotiation phases, and we share evidence of the effectiveness of the Pocket Negotiator.
Koen V. Hindriks
added an update
Koen V. Hindriks
added a project goal
To develop a new type of human-machine collaborative system that combines the strengths of human and machine and reduces their weaknesses in negotiation. Fundamental in these systems will be that user and machine explicitly share a generic task model and that such systems are to support humans in coping with emotions and moods in human-human interactions. For this purpose we will contribute new concepts, methods and techniques. For integrative bargaining we will develop such a system, called a Pocket Negotiator, to collaborate with human negotiators.