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Autonomous Learning in Mobile Cognitive Machines

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Seoul National University Seoul Korea, South

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Intelligence is a capability ascribed typically to animals, but not usually to plants. Animals can move while plants do not. Is the mobility anecessary condition or driving force for the emergence of intelligence The researchers hypothesize that mobility plays a foundational role inevolving animal and human intelligence, thus, is fundamentally important in understanding and creating embodied cognitive systems. In thisproject, the researchers aim to develop a new class of machine learning algorithms for mobile cognitive systems that actively collect data by sensing and interacting with the environment. They envision a new paradigm of autonomous AI that overcomes the previous AI paradigms of top-downrule-driven symbolic and bottom-updata-driven statistical systems. Inspired by the dual process theory of mind. They use mobile robot platforms to investigate the autonomous learning algorithms and demonstrate their capability in real-world home environments. The hypothesis of the brain being evolved to support its mobility has been raised. In fact, as the project progressed, the researchers discovered that if one of the perception-action-learning is missing or malfunctioning, maintaining the full ability of the robot was almost impossible in functioning in given scenarios. However, the researchers believe that even though perception is very important, if it is unable to perform actions in the environment, the perception ability almost loses its purpose for mobile robots in a home environment. In the basic year of this project, the researchers achieved a basic system for mobile robots to perceive, act and learn within the environment. They believe that using this system as a base, developing higher functions like memory and planning could be attained, which would be a significant step forward to achieving a truly human-level AI.

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Technical Report,26 Aug 2016,25 Aug 2017



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Approved For Public Release;

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