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

Building a Semantic Tendering System

In the new B2B e-commerce arena, applications such as auctions and data exchange are growing rapidly. However, Web content is currently designed for human consumption rather than computer manipulation. This limits the possibility of Web automation. Fortunately, the new development of the Semantic Web that allows Web pages to provide information not only in terms of their content, but also in terms of the properties of that content, can be used for automation. Electronic tendering systems are among the successfully commercial systems that can tremendously benefit from the availability of Semantic Web. This study proposes an e-tendering system that uses the Semantic Web to investigate the automatic negotiation process. The system is built in a P2P environment to simulate a two-player negotiation. It is found that the ontology of semantic information can be used to locate qualified suppliers and precede negotiation. The bargaining power of each party is then determined by the relative magnitude of the negotiators’ respective costs of haggling and the utility that varies with the degree of risk preference. Our experiments showed that applying automatic negotiation strategies to e-tendering system in semantic web can reflect the risk preference of the participants