1. University of Minho School of Engineering Computer Science and Technology Center Uma Escola a Reinventar o Futuro – Semana da Escola de Engenharia - 24 a 27 de Outubro de 2011 DAVIDE RUA CARNEIRO * Supervisors: Paulo Novais, José Neves * dcarneiro@di.uminho.pt AN AGENT-BASED ARCHITECTURE FOR ONLINE DISPUTE RESOLUTION SERVICES Alternative Dispute Resolution Retrieval of Information In order for parties to make good decisions they should have access to a set of important information. Using a Case-based Reasoning (CBR) approach, the system is able to generate information about: -BATNA – Best Alternative to a Negotiated Agreement; -WATNA – Worst Alternative to a Negotiated Agreement; -MLATNA – Most Likely Alternative to a Negotiated Agreement; -Similar cases – Past cases that are similar to the current one and may be of interest; -ZOPA – Zone of Potential Agreement; Solving the Conflict When parties have enough information and the system has solutions to suggest (obtained either through CBR or GA) the conflict resolution can start. It consists of a negotiation in which the system or the parties successively propose solutions using mobile or web interfaces. Generation of Solutions Sometimes, case-based approaches can have drawbacks, mainly when there is a poor database. In that sense, we developed a module based on a Genetic Algorithm (GA) to generate solutions for the resolution of the conflict. In the past, contracts were signed in the physical presence of all the parties. Now, contracts are signed electronically and sometimes even automatically, with the parties possibly anywhere in the world. This poses new challenges to the legal systems. Several approaches exist that aim to solve conflicts out of courts, namely Arbitration, Negotiation, Mediation or Facilitation. All of them aim to be a cheaper and faster alternative to litigation, which is nowadays slow and inefficient. However, these already traditional approaches can be improved with the support of technology and, specifically through Artificial Intelligence techniques. Environments for Conflict Resolution In the search for more efficient methods we are developing the concept of Environments for Conflict Resolution. In this approach, Ambient Intelligence is used to collect context information from the context of interaction that can support the lifecycle of the conflict resolution platform, allowing the software agents to make better and more informed decisions. Under this approach, each solution is seen as an individual of the population, which is evolved through the successive application of three genetic operators: Crossover, Heredity, and Mutation. These operators enable the natural emergence of species: lines of evolution that generate solutions that are better for a given party. This is denoted by the colors of the individuals. During the negotiation the solutions generated can then be proposed to the parties according to the changes in the context of interaction (e.g. levels of stress, personal conflict style). This work is included in TIARAC - Telematics and Artificial Intelligence in Alternative Conflict Resolution PTDC/JUR/71354/2006, a research project supported by FCT. The work of Davide Carneiro is also supported by a doctoral grant (SFRH/BD/64890/2009). islab.di.uminho.pt