ABIBA: An agent-based computing system for behaviour analysis used in human-agent interaction

Abstract

We build an agent-based system for supporting correlation analysis between human behavioural and non-behavioural patterns. A novel social norm specification language is leveraged to create an interaction model based communication engine for choreographing distributed systems, offering a communication environment for multiple interacting players. Categorising sets of players based on their interaction behaviours allows labelling the other patterns, which the system uses to further its understanding relationship between the two traits. While existing analysis methods are manually applied, non-user-editable and typically opaque, the system offers an end-to-end computing framework and protocols which are modifiable for specific users. Evaluation for this system relies on tests for categories of people who are mentally depressed, where traditional questionnaire-based methods are superseded by methods that use more objective behavioural tests. This approach to evaluation through behavioural experimentation is intended not only to classify sub-types of depression cases which would facilitate elucidation of aetiology but evaluates system performance in a real-world scenario.