Developing a corpus of strategic conversation in The Settlers of Catan

International audienceWe describe a dialogue model and an implemented annotation scheme for a pilot corpus of annotated online chats concerning bargaining negotiations in the game The Settlers of Catan. We will use this model and data to analyze how conversations proceed in the absence of strong forms of cooperativity, where agents have diverging motives. Here we concentrate on the description of our annotation scheme for negotiation dialogues, illustrated with our pilot data, and some perspectives for future research on the issue

Towards Integration of Cognitive Models in Dialogue Management: Designing the Virtual Negotiation Coach Application

This paper presents an approach to flexible and adaptive dialogue management driven by cognitive modelling of human dialogue behaviour. Artificial intelligent agents, based on the ACT-R cognitive architecture, together with human actors are participating in a (meta)cognitive skills training within a negotiation scenario. The agent  employs instance-based learning to decide about its own actions and to reflect on the behaviour of the opponent. We show that task-related actions can be handled by a cognitive agent who is a plausible dialogue partner.  Separating task-related and dialogue control actions enables the application of sophisticated models along with a flexible architecture  in which  various alternative modelling methods can be combined. We evaluated the proposed approach with users assessing  the relative contribution of various factors to the overall usability of a dialogue system. Subjective perception of effectiveness, efficiency and satisfaction were correlated with various objective performance metrics, e.g. number of (in)appropriate system responses, recovery strategies, and interaction pace. It was observed that the dialogue system usability is determined most by the quality of agreements reached in terms of estimated Pareto optimality, by the user's negotiation strategies selected, and by the quality of system recognition, interpretation and responses. We compared human-human and human-agent performance with respect to the number and quality of agreements reached, estimated cooperativeness level, and frequency of accepted negative outcomes. Evaluation experiments showed promising, consistently positive results throughout the range of the relevant scales

Social Mental Shaping: Modelling the Impact of Sociality on Autonomous Agents' Mental States

This paper presents a framework that captures how the social nature of agents that are situated in a multi-agent environment impacts upon their individual mental states. Roles and relationships provide an abstraction upon which we develop the notion of social mental shaping. This allows us to extend the standard Belief-Desire-Intention model to account for how common social phenomena (e.g. cooperation, collaborative problem-solving and negotiation) can be integrated into a unified theoretical perspective that reflects a fully explicated model of the autonomous agent's mental state

Software Agents for Electronic Marketplaces: Current and Future Research Directions

The premise of software agents to define the structural and operational models of the virtual marketplace of the future can account for the increased interest regarding their application in areas where they can add substantial value in terms of automation and functionality. At the heart of such a marketplace rests an ontology modeling the domain upon which a nucleus of agent-based services can be constructed. Negotiation services hold the dominant position in terms of the attention they have received in research. Complementary to them, but no less important, are the advising services representing support functionality that is required throughout the cycle of a deal; from the expressed intention of the two parties to eventual maturity and closure. In this paper we focus on research trends and on their possible future development for ontologies and the above service categories emphasizing on the role of software agents in this context. A review and analysis of past and present works helps to formulate sets of questions that future research will seek to address

A Discussion of Interactive Storytelling Techniques for Use in a Serious Game

This report addresses a collection of interactive storytelling systems to provide an overview of state-of-the-art methods of narrative management and of enabling social interaction between users and virtual agents. This is done to inform the construction of a social cues and training demonstrator (a serious game) that enables its users to improve their social behaviour. In this report, a distinction is made between strong story and strong autonomy approaches to narrative management. The former rely on central management of the narrative through drama managers, not giving their agents much freedom. Inversely, the latter focus on the autonomy of agents, without explicit top-down control over the narrative. The autonomy of such agents allows an unscripted narrative to emerge from the user's interaction with the system. The trade-off between a strict storyline and freedom of action in these approaches is called the narrative paradox. It is concluded that a strong autonomy approach can feature social behaviour of agents more easily than a strong story one, because it is inherent with this approach that its agents have more complex models. For the demonstrator, some control over the narrative is required to let its users reach given goals in the created scenarios. Therefore, our future work will focus on creating a hybrid approach that enables agents to direct the story autonomously