Using Game Description Language for mediated dispute resolution

Theory and Decision, 1988

The objective of this paper is to introduce a flexible approach to the structuring of negotiations. The process of negotiations with its intricacies is discussed, and drawbacks of quantitative methods are analyzed. The decomposition of the negotiation process into a certain hierarchical structure is presented. This structure is represented with 'and/or' trees used for knowledge representation in artificial intelligence. The definitions of flexibility and reactions to the opponent's moves are introduced with the help of a rule-based formalism. The implications of these definitions for the analysis of the negotiation process are presented. The approach is illustrated with a set of hypothetical examples.

informatik.rwth-aachen.de

Declarative Agent Languages and Technologies V, 2008

The workshop on Declarative Agent Languages and Technologies (DALT), in its fifth edition this year, is a well-established forum for researchers interested in sharing their experiences in combining declarative and formal approaches with engineering and technology aspects of agents and multi-agent systems.

Mediation is a process, in which both parties agree to resolve their dispute by negotiating over alternative solutions presented by a mediator. In order to construct such solutions, mediation brings more information and knowledge, and, if possible, resources to the negotiation table. The contribution of this paper is the automated mediation machinery which does that. It presents an argumentation-based mediation approach that extends the logic-based approach to argumentation-based negotiation involving BDI agents. The paper describes the mediation algorithm. For comparison it illustrates the method with a case study used in an earlier work. It demonstrates how the computational mediator can deal with realistic situations in which the negotiating agents would otherwise fail due to lack of knowledge and/or resources.

Negotiation is a central process in an agent society where autonomous agents have to cooperate in order to resolve conflicting interests and yet compete to divide limited resources. A direct dialogical exchange of information between agents usually leads to competitive forms of negotiation where the most powerful agents win. Alternatively, an intelligent mediated interaction may better achieve the goal of reaching a common agreement and supporting cooperative negotiation. In both cases argumentation is the reference framework to rationally manage conflicting knowledge or objectives, a framework which provides the fundamental abstraction “argument” to exchange pieces of information. In this paper we present a novel conceptual framework for negotiation dialogues using argumentation between autonomous software agents which enables their dialogues to be automated. The framework, called SANA (Supporting Artifacts for Negotiation with Argumentation), incorporates intelligent components able to assist the agent participants to reach agreement by inferring mutually-acceptable proposals. The framework also permits agents to engage in negotiation dialogues with each other, generating and exchanging proposed deals and arguments for and against these proposals. Acceptability of proposals is then assessed in terms of an agreed argumentation framework semantics. We present the architecture of our framework, along with the syntax, and outline denotational semantics of an associated agent interaction protocol, called SANAP.

This paper presents a simple interactive negotiation approach for conflicts in everyday life with incomplete information. We focus on mediation to obtain an agreement while going through alternating offers over a finite time bargaining game. The mediator searches and proposes a jointly optimal negotiation text for all players participating in the negotiation process based on their conditional preference networks (CP-nets). The players make a decision whether to accept or reject by examining their utility CP-nets. We develop two algorithms for the mediator and the players. If the first negotiation text cannot be accepted by all players, the mediator offers the next negotiation texts by searching for jointly optimal solutions. This negotiation process continues until an agreement is achieved or a deadline is reached. This proposed approach can support multi-issue, multi-party negotiation to achieve an agreement during a finite number of rounds with near optimal outcomes.

Lecture Notes in Computer Science, 2011

In virtually every environment there is the chance that, sooner or later, a dispute will arise. Disputes can take place in the most different scenarios and concern the most different subjects. With the advent of the telecommunication technologies, disputes also started to take place in virtual environments. In order to settle these new disputes, Online Dispute Resolution tools started to emerge. In this paper we present one of such tools, aimed at supporting mediation between two or more parties. Specifically, this tool looks at past known mediation processes and tries to guide the process into a successful outcome. It targets scenarios in which one or more party exhibits avoiding or uncooperative conflict styles, i.e., the party cannot or is not willing to generate valid proposals for dispute resolution.

Mediation is an important paradigm for dispute resolution. If done properly, it can lead to "win-win" situations and benefit all parties. Thus, the advantage of designing a proficient automated mediator capable of interacting with people during their negotiations is of great importance. Yet, succeeding in this task is difficult due to the diversity of people and their bounded rationality. To be successful, the mediator must take this into account, and propose solutions deemed relevant, or otherwise, lose the focus and trust of the negotiators. In this paper we present AniMed. AniMed is 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 more than 100 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.

Knowledge and Information Systems, 2013

The growing use of Information Technology in the commercial arena leads to an urgent need to find alternatives to traditional dispute resolution. New tools from fields such as Artificial Intelligence should be considered in the process of developing novel Online Dispute Resolution platforms, in order to make the ligation process simpler, faster and conform with the new virtual environments. In this work, we describe UMCourt, a project built around two sub-fields of Artificial Intelligence research: Multi-agent Systems and Case-based Reasoning, aimed at fostering the development of tools for Online Dispute Resolution. This is then used to accomplish several objectives, from suggesting solutions to new disputes based on the observation of past similar disputes, to the improvement of the negotiation and mediation processes that may follow. The main objective of this work is to develop autonomous tools that can increase the effectiveness of the dispute resolution processes, namely by increasing the amount of meaningful information that is available for the parties.