Supporting the Design of General Automated Negotiators

Lin, Raz; Kraus, Sarit; Tykhonov, Dmytro; Hindriks, Koen V.; Jonker, Catholijn M.

doi:10.1007/978-3-642-15612-0_4

Cited by 20 publications

(19 citation statements)

References 23 publications

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“…For our experimental setup we employed Genius (General Environment for Negotiation with Intelligent multi-purpose Usage Simulation) [13]. This environment, which is also used in ANAC, facilitates the design and evaluation of automated negotiators' strategies.…”

Section: Methodsmentioning

confidence: 99%

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Towards a Quantitative Concession-Based Classification Method of Negotiation Strategies

Baarslag

Hindriks

Jonker

2011

Lecture Notes in Computer Science

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Abstract. 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.

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Section: Methodsmentioning

confidence: 99%

“…The second domain taken from [13,14] involves a case where England and Zimbabwe negotiate an agreement on tobacco control. The leaders of both countries must reach an agreement on five issues.…”

Section: Domainsmentioning

confidence: 99%

Towards a Quantitative Concession-Based Classification Method of Negotiation Strategies

Baarslag

Hindriks

Jonker

2011

Lecture Notes in Computer Science

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“…The second domain taken from [17,18] involves a case where England and Zimbabwe negotiate an agreement on tobacco control. The leaders of both countries must reach an agreement on five issues.…”

Section: Domainsmentioning

confidence: 99%

Acceptance Conditions in Automated Negotiation

Baarslag

Hindriks

Jonker

2013

Studies in Computational Intelligence

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Abstract. In every negotiation with a deadline, one of the negotiating parties has to accept an offer to avoid a break off. A break off is usually an undesirable outcome for both parties, therefore it is important that a negotiator employs a proficient mechanism to decide under which conditions to accept. When designing such conditions one is faced with the acceptance dilemma: accepting the current offer may be suboptimal, as better offers may still be presented. On the other hand, accepting too late may prevent an agreement from being reached, resulting in a break off with no gain for either party. Motivated by the challenges of bilateral negotiations between automated agents and by the results and insights of the automated negotiating agents competition (ANAC), we classify and compare state-of-the-art generic acceptance conditions. We focus on decoupled acceptance conditions, i.e. conditions that do not depend on the bidding strategy that is used. We performed extensive experiments to compare the performance of acceptance conditions in combination with a broad range of bidding strategies and negotiation domains. Furthermore we propose new acceptance conditions and we demonstrate that they outperform the other conditions that we study. In particular, it is shown that they outperform the standard acceptance condition of comparing the current offer with the offer the agent is ready to send out. We also provide insight in to why some conditions work better than others and investigate correlations between the properties of the negotiation environment and the efficacy of acceptance conditions.

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“…The design of AniMed is built on top of the GENIUS infrastructure, which is an integrated environment for supporting the design of generic automated negotiators [2]. This environment is rich and supports bilateral multi-issue and multi-attribute negotiations, both with human counterparts and automated agents.…”

Section: Mediator Designmentioning

confidence: 99%

“…Thus, AniMed has a generic strategy mechanism, allowing it to be matched and mediate proficiently with many possible types of negotiators without any restriction to any specific domain. Lastly, as AniMed was built on top of GENIUS, a generic negotiation framework [2], it will be available for the public and can be modified and used in numerous domains.…”

Section: Introductionmentioning

confidence: 99%

Bridging the Gap: Face-to-Face Negotiations with an Automated Mediator

2011

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Abstract-Mediation is an important paradigm for dispute resolution. It can lead to "win-win" situations and benefit all parties. Yet, when people negotiate they demonstrate bounded rationality in their actions and diversity in their behaviors. This increases the difficulty to design automated mediators. To be successful, the mediator must take this into account and propose solutions deemed relevant, otherwise it will lose the focus and trust of the negotiators. To tackle these difficulties we present AniMed -an automated animated mediator, incorporated with a novel proposal generation strategy, aimed to increase the social benefit of the negotiating parties. To validate the benefits of using AniMed in negotiations, experiments were conducted with 130 people negotiating with each other. The results demonstrate the significant increase both in the social welfare and the individual utilities of both parties, compared to negotiations in which another state-of-the-art automated mediator or no mediator was involved.

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Supporting the Design of General Automated Negotiators

Cited by 20 publications

References 23 publications

Towards a Quantitative Concession-Based Classification Method of Negotiation Strategies

Towards a Quantitative Concession-Based Classification Method of Negotiation Strategies

Acceptance Conditions in Automated Negotiation

Bridging the Gap: Face-to-Face Negotiations with an Automated Mediator

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