Poster for AAMAS 2018: Communicative listener feedback in human–agent interaction: Artificial speakers need to be attentive and adaptive

Poster accompanying the following paper:<div><br><div>Buschmeier, H. & Kopp, S. (2018). Communicative listener feedback in human–agent interaction: artificial speakers need to be attentive and adaptive. In <i>Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems</i>, pp. 1213–1221, Stockholm, Sweden.</div></div

A model for dynamic minimal mentalising in dialogue

<p>Buschmeier, H. & Kopp, S. (2014). A model for dynamic minimal mentalizing in dialogue. In <em>Proceedings of the 12th Biannual Conference of the German Cognitive Science Society,</em> pp. S32–S33, Tübingen, Germany. </p> <p>Poster presented at KogWis 2014, 1-4 October 2014, Tübingen Germany.</p

Unveiling the Information State with a Bayesian Model of the Listener

<p>Buschmeier, H., & Kopp, S. (2011). Unveiling the information state with a Bayesian model of the listener. In <em>SemDial 2011: Proceedings of the 15th Workshop on the Semantics and Pragmatics of Dialogue,</em> pp. 178–179, Los Angeles, CA, USA.</p> <p>Poster presented at SemDial 2011, September 21–23, 2011, Los Angeles, CA, USA.</p

A spreading-activation model of dynamic multimodal memory stabilization

<p>Poster on “A spreading-activation model of dynamic multimodal memory stabilization” presented at the Interdisciplinary College 2014 in Günne, Germany.</p

Socially cooperative behavior for artificial companions for elderly and cognitively impaired people

<p>Yaghoubzadeh, R., Buschmeier, H., & Kopp, S. (2015). Socially cooperative behavior for artificial companions for elderly and cognitively impaired people. In <em>Proceedings of the International Symposium on Companion-Technology,</em> Ulm, Germany.</p> <p>Poster presented at ISCT 2015, 23.–25. September 2015, Ulm, Germany.</p

Number of scripted drink orders, drink orders detected by the sensors and number of correctly served drinks.

<p>Number of scripted drink orders, drink orders detected by the sensors and number of correctly served drinks.</p

Bartending robot.

<p>The robot is shown at its bar about to grab a bottle of water for serving.</p

Setting of the study.

<p>The setting for the ghost participants including the information panel, eye tracker, control panel and eye tracker control screen. The participant wears passive noise insulating headphones.</p

Relative dwell times on indicators.

<p>Relative dwell times on indicators.</p

Number of cases, serving time (RT), their participant-wise <i>z</i>-scores and the corresponding standard deviations from the first appearance of the customers until the first drink in the trial was served as a function of the type of request, preceding menu related questions and condition (<i>certain</i>/<i>uncertain</i>).

<p>Number of cases, serving time (RT), their participant-wise <i>z</i>-scores and the corresponding standard deviations from the first appearance of the customers until the first drink in the trial was served as a function of the type of request, preceding menu related questions and condition (<i>certain</i>/<i>uncertain</i>).</p