AISep 8, 2020
Linear Temporal Public Announcement Logic: a new perspective for reasoning about the knowledge of multi-classifiersAmirhoshang Hoseinpour Dehkordi, Majid Alizadeh, Ali Movaghar
In this note, a formal transition system model called LTPAL to extract knowledge in a classification process is suggested. The model combines the Public Announcement Logic (PAL) and the Linear Temporal Logic (LTL). In the model, first, we consider classifiers, which capture single-framed data. Next, we took classifiers for data-stream data input into consideration. Finally, we formalize natural language properties in LTPAL with a video-stream object detection sample.
AIJul 3, 2020
Meet MASKS: A novel Multi-Classifier's verification approachAmirhoshang Hoseinpour Dehkordi, Majid Alizadeh, Ali Movaghar
In this study, a new ensemble approach for classifiers is introduced. A verification method for better error elimination is developed through the integration of multiple classifiers. A multi-agent system comprised of multiple classifiers is designed to verify the satisfaction of the safety property. In order to examine the reasoning concerning the aggregation of the distributed knowledge, a logical model has been proposed. To verify predefined properties, a Multi-Agent Systems' Knowledge-Sharing algorithm (MASKS) has been formulated and developed. As a rigorous evaluation, we applied this model to the Fashion-MNIST, MNIST, and Fruit-360 datasets, where it reduced the error rate to approximately one-tenth of the individual classifiers.