| 研究実績の概要 |
In this period the possibility of using multiple agents in the Fuzzy Rule Interpolation-based Reinforcement Learning (FRI-RL) and running them distributed in parallel was investigated. As the FRI-RL knowledge extraction method is inherently sequential, some sub-results can be different in the parallel version, but still providing a sufficient solution. This way the knowledge extraction can be performed much faster, therefore using the method on problems with a high dimension count becomes practical. Also, a possible bridging interface between the behaviour simulation model (Strange Situation Test (SST) realized with an FRI-based fuzzy automaton) and real physical robots have been partly designed and implemented. Experimenting with real physical robots is underway. Furthermore a suitable indoor localization system was constructed and adapted to the needs of the planned Human-Robot Interaction (HRI) scenario. This system is able to easily calibrate the indoor localization system’s virtual coordinate system to the real-world physical coordinate system, which makes our planned HRI experiments possible with real humans and mobile robots. A customized robot behaviour engine and a motion control system was developed to support the proposed artificial Strange Situation Test experiments.
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