DipGame: A challenging negotiation testbed

There is a chronic lack of shared application domains to test advanced research models and agent negotiation architectures in Multiagent Systems. In this paper we introduce a friendly testbed for that purpose. The testbed is based on The Diplomacy Game where negotiation and the relationships between players play an essential role. The testbed profits from the existence of a large community of human players that know the game and can easily provide data for experiments. We explain the infrastructure in the paper and make it freely available to the AI community. © 2011 Elsevier Ltd. All rights reserved.Research supported by the Agreement Technologies CONSOLIDER project under contract CSD2007-0022 and INGENIO 2010, by the Agreement Technologies COST Action, IC0801, and by the Generalitat de Catalunya under the grant 2009-SGR-1434.Peer Reviewe

A dialogical model for collaborative decision making based on compromises

Abstract. In this paper, we deal with group decision making and propose a model of dialogue among agents that have different knowledge and preferences, but are willing to compromise in order to collaboratively reach a common decision. Agents participating in the dialogue use internal reasoning to resolve conflicts emerging in their knowledge during communication and to reach a decision that requires the least compromises. Our approach has significant potential, as it may allow targeted knowledge exchange, partial disclosure of information and efficient or informed decision-making depending on the topic of the agents' discussion

Turning Unstructured and Incoherent Group Discussion into DATree: A TBL Coherence Analysis Approach

Despite the rapid growth of user-generated unstructured text from online group discussions, business decision-makers are facing the challenge of understanding its highly incoherent content. Coherence analysis attempts to reconstruct the order of discussion messages. However, existing methods only focus on system and cohesion features. While they work with asynchronous discussions, they fail with synchronous discussions because these features rarely appear. We believe that discussion logic features play an important role in coherence analysis. Therefore, we propose a TCA method for coherence analysis, which is composed of a novel message similarity measure algorithm, a subtopic segmentation algorithm and a TBL-based classification algorithm. System, cohesion and discussion logic features are all incorporated into our TCA method. Results from experiments showed that the TCA method achieved significantly better performance than existing methods. Furthermore, we illustrate that the DATree generated by the TCA method can enhance decision-makers’ content analysis capability