Abstract
Most agents obtain knowledges from natural scenes through some single preestablished rules. In practice, those single rules can’t achieve the aim to freely awareness the natural scenes, such as the visual scenes. Inspired by biological visual cortex (V1) and higher brain areas perceiving visual features, in this paper we propose an improved visual awareness module, called as visual scenes mining module, for the agent ABGP-CNN in order to directly mine the visual scenes information. Then ABGP-CNN with the visual scenes mining module is deployed on a toy car. The visual information mining from the nature scenes is served as the knowledges of the agent ABGP-CNN to drive the toy car. The toy car deployed the agent ABGP-CNN can easily understand the special natural visual scenes, and has the ability to plan its behaviors according to the visual information mining from the nature scenes. The application of the agent ABGP-CNN with visual scenes mining module enhances the capability of communication between the toy car and the natural visual scenes.
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Ma, G., Tang, Z., Yang, X., Shi, Z., Yang, K. (2017). Visual Scenes Mining for Agent Awareness Module. In: Perner, P. (eds) Advances in Data Mining. Applications and Theoretical Aspects. ICDM 2017. Lecture Notes in Computer Science(), vol 10357. Springer, Cham. https://doi.org/10.1007/978-3-319-62701-4_13
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DOI: https://doi.org/10.1007/978-3-319-62701-4_13
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