Affecta-context: The Context-Guided Behavior Adaptation Framework

Research output: Contribution to conference - NOT published in proceeding or journalPaperResearchpeer-review


This paper presents Affecta-context, a general framework to facilitate behavior adaptation for social robots. The framework uses information about the physical context to guide its behaviors in human-robot interactions. It consists of two parts: one that represents encountered contexts and one that learns to prioritize between behaviors through human-robot interactions.
As physical contexts are encountered the framework clusters them by their measured physical properties. In each context, the framework learns to prioritize between behaviors to optimize the physical attributes of the robot's behavior in line with its current environment and the preferences of the users it interacts with.
This paper illlustrates the abilities of the Affecta-context framework by enabling a robot to autonomously learn the prioritization of discrete behaviors. This was achieved by training across 72 interactions in two different physical contexts with 6 different human test participants. The paper demonstrates the trained Affecta-context framework by verifying the robot's ability to generalize over the input and to match its behaviors to a previously unvisited physical context.
Original languageEnglish
Publication date4 Jul 2023
Publication statusPublished - 4 Jul 2023
EventThe 18th International Conference on Intelligent Autonomous Systems - Suwon Convention Center, Suwon, Korea, Republic of
Duration: 4 Jul 20238 Jul 2023
Conference number: 18


ConferenceThe 18th International Conference on Intelligent Autonomous Systems
LocationSuwon Convention Center
Country/TerritoryKorea, Republic of
Internet address


  • Contact
  • Behaviour
  • Affective impact
  • Robotics
  • learning
  • Autonomous systems


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