AutoMed: an automated mediator for multi-issue bilateral negotiations

Chalamish, Michal; Kraus, Sarit

doi:10.1007/s10458-010-9165-y

Cited by 36 publications

(22 citation statements)

References 21 publications

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“…This uncertainty was also shared by the mediator, that had information solely on the preference relation between the issues and values under negotiation. AniMed significantly increased the individual utility score and the social welfare, measured by the sum of utilities, of both negotiators, compared to experiments in which another state-of-the-art mediator [3] or no mediator were involved. The results also indicate that while people are content with the solutions they achieve without any mediator involved, better solutions can be achieved when AniMed is present.…”

Section: Introductionmentioning

confidence: 89%

“…One experiment involved matching people without any mediator. In another experiment we matched two people with a simple automated mediator, AutoMed, suggested by Chalamish and Kraus [3]. They demonstrated that this mediator enables the negotiators to achieve more satisfactory solutions in environments where only messages are exchanged.…”

Section: Methodsmentioning

confidence: 99%

“…AutoMed [3] is an automated mediator that most resembles our proposed mediator. AutoMed monitors the exchange of offers and actively suggests possible solutions.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

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

2011

Self Cite

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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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Section: Introductionmentioning

confidence: 89%

Section: Methodsmentioning

confidence: 99%

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

2011

Self Cite

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“…For example, there is a growing literature focused on optimally managing negotiations between strategic, self-interested agents (Brafman & Tennenholtz, 1996;Chalamish & Kraus, 2012;Lopez-Carmona, Marsa-Maestre, Klein, & Ito, 2012). The primary difference between our paper and the current literature is that our bargaining game is unstructured, while the others use a structured game.…”

Section: Contribution Of This Papermentioning

confidence: 98%

Predicting Behavior in Unstructured Bargaining with a Probability Distribution

Wolpert¹,

Bono²

2013

jair

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In experimental tests of human behavior in unstructured bargaining games, typically many joint utility outcomes are found to occur, not just one. This suggests we predict the outcome of such a game as a probability distribution. This is in contrast to what is conventionally done (e.g, in the Nash bargaining solution), which is predict a single outcome. We show how to translate Nash's bargaining axioms to provide a distribution over outcomes rather than a single outcome. We then prove that a subset of those axioms forces the distribution over utility outcomes to be a power-law distribution. Unlike Nash's original result, our result holds even if the feasible set is finite. When the feasible set is convex and comprehensive, the mode of the power law distribution is the Harsanyi bargaining solution, and if we require symmetry it is the Nash bargaining solution. However, in general these modes of the joint utility distribution are not the experimentalist's Bayesoptimal predictions for the joint utility. Nor are the bargains corresponding to the modes of those joint utility distributions the modes of the distribution over bargains in general, since more than one bargain may result in the same joint utility. After introducing distributional bargaining solution concepts, we show how an external regulator can use them to optimally design an unstructured bargaining scenario. Throughout we demonstrate our analysis in computational experiments involving flight rerouting negotiations in the National Airspace System. We emphasize that while our results are formulated for unstructured bargaining, they can also be used to make predictions for noncooperative games where the modeler knows the utility functions of the players over possible outcomes of the game, but does not know the move spaces the players use to determine those outcomes.

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“…Within the field of artificial intelligence (AI), there is an active effort of research for studying negotiation processes using agent based modeling [20] and developing support tools for mediation [5]. These, together with the recent formulation of a mediation framework by Simoff et al [32], provide a theoretical basis for a computational approach to mediation, which can promisingly address the aspects mentioned above.…”

mentioning

confidence: 99%

CBR with Commonsense Reasoning and Structure Mapping: An Application to Mediation

Baydin

et al. 2011

Case-Based Reasoning Research and Development

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Abstract. Mediation is an important method in dispute resolution. We implement a case based reasoning approach to mediation integrating analogical and commonsense reasoning components that allow an artificial mediation agent to satisfy requirements expected from a human mediator, in particular: utilizing experience with cases in different domains; and structurally transforming the set of issues for a better solution. We utilize a case structure based on ontologies reflecting the perceptions of the parties in dispute. The analogical reasoning component, employing the Structure Mapping Theory from psychology, provides a flexibility to respond innovatively in unusual circumstances, in contrast with conventional approaches confined into specialized problem domains. We aim to build a mediation case base incorporating real world instances ranging from interpersonal or intergroup disputes to international conflicts.

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AutoMed: an automated mediator for multi-issue bilateral negotiations

Cited by 36 publications

References 21 publications

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

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

Predicting Behavior in Unstructured Bargaining with a Probability Distribution

CBR with Commonsense Reasoning and Structure Mapping: An Application to Mediation

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