Towards a Companion System Incorporating Human Planning Behavior – A Qualitative Analysis of Human Strategies

Towards a Companion System Incorporating Human Planning Behavior – A Qualitative Analysis of Human Strategies. Leichtmann, B., Bercher, P., Höller, D., Behnke, G., Biundo, S., Nitsch, V., & Baumann, M. In Proceedings of the 3rd Transdisciplinary Conference on Support Technologies (TCST 2018), pages 89–98, 2018. This paper won the TCST 2018 Best Paper Award

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User-friendly Companion Systems require Artificial Intelligence planning to take into account human planning behavior. We conducted a qualitative exploratory study of human planning in a knowledge rich, real-world scenario. Participants were tasked with setting up a home theater. The effect of strategy knowledge on problem solving was investigated by comparing the performance of two groups: one group (n = 23) with strategy instructions for problem solving and a control group without such instructions (n = 16). We inductively identify behavioral patterns for human strategy use through Markov matrices. Based on the results, we derive implications for the design of planning-based assistance systems.

@InProceedings{Leichtmann2018HumanPlanningBehavior,
   author     = {Benedikt Leichtmann and Pascal Bercher and Daniel H{\"o}ller and Gregor Behnke and Susanne Biundo and Verena Nitsch and Martin Baumann},
   title      = {Towards a Companion System Incorporating Human Planning Behavior -- A Qualitative Analysis of Human Strategies},
   year       = {2018},
   pages      = {89--98},
   booktitle  = {Proceedings of the 3rd Transdisciplinary Conference on Support Technologies (TCST 2018)},
   note       = {<b><i>This paper won the TCST 2018 Best Paper Award</i></b>},
   abstract   = {User-friendly Companion Systems require Artificial Intelligence planning to take into account human planning behavior. We conducted a qualitative exploratory study of human planning in a knowledge rich, real-world scenario. Participants were tasked with setting up a home theater. The effect of strategy knowledge on problem solving was investigated by comparing the performance of two groups: one group (n = 23) with strategy instructions for problem solving and a control group without such instructions (n = 16). We inductively identify behavioral patterns for human strategy use through Markov matrices. Based on the results, we derive implications for the design of planning-based assistance systems.},
   url_Paper  = {https://bercher.net/publications/2018/Leichtmann2018HumanPlanningBehavior.pdf},
   url_Slides = {https://bercher.net/publications/2018/Leichtmann2018HumanPlanningBehaviorSlides.pdf},
  keywords    = {conference}
}

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