6533b830fe1ef96bd12967e3
RESEARCH PRODUCT
Agents in dynamic contexts, a system for learning plans
Valeria SeiditaPatrick HammerAntonio ChellaFrancesco LanzaPei Wangsubject
Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniReasoning systemComputer science020207 software engineeringContext (language use)02 engineering and technologyPlan (drawing)Field (computer science)Human–robot interactionPlanningWork (electrical)Human–computer interaction020204 information systems0202 electrical engineering electronic engineering information engineeringRobotBDIHuman-robot interactionJasondescription
Reproducing the human ability to cooperate and collaborate in a dynamic environment is a significant challenge in the field of human-robot teaming interaction. Generally, in this context, a robot has to adapt itself to handle unforeseen situations. The problem is runtime planning when some factors are not known before the execution starts. This work aims to show and discuss a method to handle this kind of situation. Our idea is to use the Belief-Desire-Intention agent paradigm, its the Jason reasoning cycle and a Non-Axiomatic Reasoning System. The result is a novel method that gives the robot the ability to select the best plan.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2020-03-30 |