PAPAc: a pick and place agent based on human behavioral dynamics

Maurice Lamb, Tamara Lorenz, Steven J. Harrison, Rachel Kallen, Ali Minai, Michael J. Richardson

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

5 Citations (Scopus)


Humans often engage in tasks that require or are made more efficient by coordinating with other humans. The coordination involved in these tasks can be understood in terms of the behavioral and affordance dynamics of socially embedded agents engaged in joint action activities. Behavioral dynamics provide mathematical (differential equation) models of human behavior and interaction and affordance dynamics identify and model the ways that an agent's action capabilities evolve over time. Taken together, models of human joint-action based on these approaches may provide a basis for developing robust, natural, and easy to engage artificial agents. In this paper we introduce behavioral and affordance dynamics models of human joint action in a pick-and-place task. Based on these models we provide a proof of concept pick-and-place artificial agent and implement the agent in a 3D virtual environment to interact with human co-actors.
Original languageEnglish
Title of host publicationHAI '17
Subtitle of host publicationProceedings of the 5th International Conference on Human Agent Interaction
Place of PublicationNew York, NY
Number of pages11
ISBN (Electronic)9781450351133
Publication statusPublished - 2017
Externally publishedYes
EventInternational Conference on Human Agent Interaction (5th : 2017) - Bielefeld, Germany
Duration: 17 Oct 201720 Oct 2017


ConferenceInternational Conference on Human Agent Interaction (5th : 2017)


  • human-agent interaction
  • pick-and-place
  • behavioral dynamics
  • affordances
  • human-centered algorithms
  • joint action


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