Online Spatial Concept and Lexical Acquisition with Simultaneous Localization and Mapping
TABLE II: Evaluation values of NMI and EAR for each method
['Methods', 'NMI  [ITALIC] Ct', 'NMI  [ITALIC] it', 'EAR  [ITALIC] L', 'EAR  [ITALIC] K']
Fig. In both Ct and it, the NMI values tended to rise at the beginning. The NMI values of Ct were similar for methods (A), (B), and (C). In the NMI values for it, the proposed method (A) showed higher values than the other methods after step 30. We consider a major possible reason for the clustering results of spatial concepts. In online lexical acquisition, the word segmentation results cannot be obtained stably when training dataset is small. We consider that stable words can be obtained by further increasing the number of training steps. Fig. The average values of the estimated results of method (D) were L=18.9, K=13.1. True data was determined by a user based on teaching data. The experimental results show that the proposed method (A) was closer to the true data than other methods for both L and K.