To personalise dialogue to different users, relational agents need to learn about the users' preferences for relational cues used by the agent. In the context of a virtual advisor to reduce students' study stress, we designed a between subjects study with three groups (empathic, neutral and adaptive) who either received all cues, no cues or helpful cues only, respectively, and compared rapport and changes in study stress scores. To avoid the cold start problem, we sought to train the agent and adapt its dialogue to include or exclude 10 relational cues based on the user's responses to whether an example of each relational cue is found helpful prior to the session with the virtual advisor. The results of an experiment with 111 students show that the rapport scores for the empathic and adaptive groups were significantly higher than the neutral group; change in rapport scores was significantly higher in the adaptive group than in the empathic group. Furthermore, study stress scores significantly reduced for the adaptive and empathic groups, but not for the neutral group. We found some relationships between the number of times students found helpful what they received and other variables. We also found that the number of discrepancies and matches between what relational cues users received and what they found helpful were greatest in the adaptive group. This indicates the effectiveness of this approach for dealing with the cold start problem.

Intelligent virtual agents are being endowed with empathic behaviours to perform roles such as virtual therapists. Studies often evaluate the level of rapport established, but do not measure the therapeutic benefit and the relative advantage of empathic versus neutral behaviours. We have created two virtual (empathic/neutral) therapists. Our experiment with 63 participants consisted of one within-subjects (empathic/neutral) and one between-subjects (order) factors. Regardless of the virtual therapist used, improvements in baseline emotion were reported after the first interaction (time one) and further improvement after the second interaction (time two). Our study reveals that if the human initially expresses strong emotional feeling for a problem they are facing, rapport will be higher for the empathic therapist and the level of rapport established at the first meeting will persist regardless of whether the second encounter used empathic or neutral dialogue. Conversely, participants experiencing low emotional feeling reported greater rapport with the neutral therapist, and that level of rapport persisted in the second encounter with the alternative therapist. This study shows that an empathic agent will not necessarily build more rapport or deliver better emotional outcomes than a neutral agent. Further studies are needed to determine when tailoring and complex behaviours are justified.

This paper presents the lessons learnt during the analysis of the corporate databases developed by IBM Global Services (Australia). IBM is rated as CMM level 5. Following CMM level 4 and above practices, IBM designed several software metrics databases with associated data collection and reporting systems to manage its corporate goals. However, IBM quality staff believed the data were not as useful as they had expected. NICTA staff undertook a review of IBM's statistical process control procedures and found problems with the databases mainly due to a lack of links between the different data tables. Such problems might be avoided by using M3P variant of the GQM paradigm to define a hierarchy of goals, with project goals at the lowest level, then process goals and corporate goals at the highest level. We propose using E-R models to identify problems with existing databases and to design databases once goals have been defined.