A BDI Dialogue Agent for Social Support:
Specification and Evaluation Method
1
J.M. van der Zwaan
V. Dignum
C.M. Jonker
Delft University of Technology, P.O.Box 5010 2600 GA Delft
Abstract
An important task for empathic agents is to provide social support, that is, to help alleviate emotional distress. In this paper we specify verbal support types for a dialogue agent that provides social support, and propose an evaluation method for such an agent in a sensitive domain (cyberbullying) with a vulnerable target audience (children).
1 Introduction
Social support or comforting refers to communicative attempts to alleviate emotional distress and is aimed at increasing the well-being of people and decreasing the perceived burden of their problems. Recent de-velopments in affective computing show that empathic agents are increasingly capable of complex social and emotional dialogues. However, these dialogues are predominantly task oriented, i.e. to help the user perform a concrete task, such as finding information or learning. A comforting conversation is focussed on giving and receiving support; no concrete tasks are involved.
In our research, we are investigating how and to what extent Embodied Conversational Agents (ECAs) can provide social support. Recently, we proposed a dialogue model for social support [2]. Interaction between the agent and the user takes place in two main stages: 1) Gather information about the current situation, 2) Give advice on how to deal with the situation. This paper presents an extension of the dia-logue model by specifying strategies for verbal social support that frequently occur in online counseling conversations (sympathy, compliment, encouragement, advice, and teaching).
The extended dialogue model was implemented in a conversational agent that provides social support to victims of cyberbullying. Given the sensitivity of the application domain (cyberbullying) and the vulnera-bility of the target audience (children), a careful and thorough evaluation is highly important. Additionally this paper presents an evaluation plan or the dialogue agent. While it is tempting to think about the agent in terms of it’s potential for reducing cyberbullying, we would like to emphasize that our focus is on providing social support.
2 Verbal Social Support
To illustrate how the agent verbally expresses social support, we specify the reasoning process behind sym-pathy. The agent’s reasoning engine is modeled according to the Belief-Desire-Intention (BDI) paradigm [1]. This means the agent has beliefs (e.g., about what advice to give in which situations), goals (e.g., to give social support), and plans (e.g., to gather information about the upsetting situation). To improve the readability of the explanation, all speech acts have been translated into natural language utterances.
The information gathering phase of a comforting conversation consists of a recurring pattern of the agent asking a question, the user answering that question, and the agent acknowledging the answer. An acknowledgement is either neutral (e.g., Okay) or sympathetic. The agent expresses sympathy if it follows from his beliefs sympathy is applicable, otherwise it plays safe by staying neutral. Table 1 shows an example
1The full version of this paper has been accepted for publication at the workshop on Emotional and Empathic Agents (EEA)
Example dialogue Knowledge base Agent: Can you tell me what happened?
User: Someone is calling me names on msn Agent: That’s awful! (sympathy)
incident(type, call names). incident(method, msn). sympathy(type, call
names):-incident(type, call names). Table 1: Example dialogue fragment in which the agent expresses sympathy.
dialogue in which the agent expresses sympathy. The second column contains the contents of the agent’s belief base. After the user answers the question two incident facts are added to the agent’s belief base. The sympathy rule triggers the agent’s sympathetic response. Absence of this rule would have resulted in a neutral acknowledgement of the user’s input (e.g., I see). To enable other responses, more facts and rules have to be added to the belief base.
The other support types have been implemented in a similar manner. Like sympathy, compliment and encouragement occur in response to the answers the user gives to questions of the agent. Advice and teaching are uttered pro-actively, after the agent gathered sufficient information (what is sufficient depends on domain knowledge). For advice that requires an explanation, the agent optionally teaches the user how to execute the advice.
3 Evaluation Plan
This section describes the evaluation plan for the social support dialogue agent in the cyberbullying domain. The goal of the evaluation is to determine the extent to which users experience social support when inter-acting with the agent. The evaluation plan consists of multiple, incremental stages in which the dialogue system is improved based on the feedback from the previous stage before moving on to the next. In the first stage of the evaluation, we will perform an expert evaluation and create scenarios of common cyberbullying situations for indirect evaluation. After multiple experiments and incremental improvements on the dialogue agent we intend to involve children in the evaluation process. In the final stage of the evaluation, actual cy-berbullying victims will be involved. Experiments in which children participate will be always conducted in cooperation with and under the supervision of psychologists and online counselors. Performance of the agent will be measured with questionnaires on perceived social support and trustworthiness of the agent.
4 Conclusion
In this paper, we specified the reasoning process of a dialogue agent that verbally expresses social support. Support types sympathy, compliment and encouragement are always given in response to user input. Advice and teaching are offered pro-actively. Additionally, we presented a multi-stage evaluation method for the dialogue agent. Because cyberbullying is a sensitive topic and children are a vulnerable target audience, we will start with an expert evaluation and create scenarios of common cyberbullying situations for indi-rect evaluation. After incremental improvements on the dialogue system, children and later cyberbullying victims will be involved in the evaluation process.
Acknowledgements
This work is funded by NWO under the Responsible Innovation (RI) program via the project ‘Empowering and Protecting Children and Adolescents Against Cyberbullying’.
References
[1] P.R. Cohen and H.J. Levesque. Intention is choice with commitment. Artificial Intelligence, 42(2-3):213 – 261, 1990.
[2] J.M. van der Zwaan, V. Dignum, and C.M. Jonker. A conversation model enabling intelligent agents to give emotional support. In Studies in Computational Intelligence, 2012.
