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SERKET: An Architecture for Connecting Stochastic Models to Realize a Large-Scale Cognitive Model
2018
Frontiers in Neurorobotics
To realize human-like robot intelligence, a large-scale cognitive architecture is required for robots to understand their environment through a variety of sensors with which they are equipped. In this paper, we propose a novel framework named Serket that enables the construction of a large-scale generative model and its inferences easily by connecting sub-modules to allow the robots to acquire various capabilities through interaction with their environment and others. We consider that
doi:10.3389/fnbot.2018.00025
pmid:29997493
pmcid:PMC6028621
fatcat:c7jyjhm6t5b4rfahljkxhf5z2e