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Spatio-Temporal Case-Based Reasoning for Behavioral Selection

机译:基于时空案例的行为选择推理

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This paper presents the application of a Case-Based Reasoning (CBR) approach to the selection and modification of behavioral assemblage parameters. The goal of this research is to achieve an optimal parameterization of robotic behaviors in run-time. This increases robot performance and makes a manual configuration of parameters unnecessary. The CBR module selects a set of parameters for an active behavioral assemblage in real-time. This set of parameters fits the environment better than hand-coded ones, and its performance is monitored providing feedback for a possible re-selection of the parameters. This paper places a significant emphasis on the technical details of the CBR module and how it is integrated within a schema-based reactive navigation system. The paper also presents the results and evaluation of the system in both simulated and real-world robotic experiments.

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