Investigating Human Response, Behaviour, and Preference in Joint-Task Interaction

Alan Lindsay, Bart Craenen, Sara Dalzel-Job, Robin L. Hill, Ronald P. A. Petrick

Research output: Contribution to conferencePaperpeer-review


Human interaction relies on a wide range of signals, including non-verbal cues. In order to develop effective Explainable Planning (XAIP) agents it is important that we understand the range and utility of these communication channels. Our starting point is existing results from joint task interaction and their study in cognitive science. Our intention is that these lessons can inform the design of interaction agents—including those using planning techniques—whose behaviour is conditioned on the user's response, including affective measures of the user (i.e., explicitly incorporating the user's affective state within the planning model). We have identified several concepts at the intersection of plan-based agent behaviour and joint task interaction and have used these to design two agents: one reactive and the other partially predictive. We have designed an experiment in order to examine human behaviour and response as they interact with these agents. In this paper we present the designed study and the key questions that are being investigated. We also present the results from an empirical analysis where we examined the behaviour of the two agents for simulated users.
Original languageEnglish
Publication statusPublished - 21 Oct 2020
EventICAPS 2020 Workshop on Explainable AI Planning - online
Duration: 21 Oct 2020 → …


ConferenceICAPS 2020 Workshop on Explainable AI Planning
Abbreviated titleXAIP 2020
Period21/10/20 → …


Dive into the research topics of 'Investigating Human Response, Behaviour, and Preference in Joint-Task Interaction'. Together they form a unique fingerprint.

Cite this