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d tool. However, if one represents low-level procedures like this using another method, e.g. learned cell assemblies in a hierarchical network like DeSTIN, then it's very feasible to make Combo programs that invoke these low-level procedures, and encode higher-level actions like "pick up the cup in fro
and Benjamin Kuipers. Learning geometry from sensorimo- tor experience. In Proceedings of the First Joint Conference on Development and Learning and Epigenetic Robotics, 2012. Sol64a. Ray Solomonoff. A Formal Theory of Inductive Inference, Part I. Information and Control, 1964. Sol64b. Ray Solomonoff. A Formal Th
tiple layers, involving feedfor- ward and feedback dynamics, and adaptation of the links between the elements. An example deep learning algorithm is DeSTIN, which is being integrated with OpenCog for perception processing. • Defrosting: Restoring, into the RAM portion of an Atomspace, an Atom (or set t
Jonathan Mugan and Benjamin Kuipers. Towards the application of reinforcement learning to undirected developmental learning. International Conf. on Epigenetic Robotics, 2008. MK09. Jonathan Mugan and Benjamin Kuipers. Autonomously learning an action hierarchy using a learned qualitative state representation. L IC
ltiple layers, involving feedfor- ward and feedback dynamics, and adaptation of the links between the elements. An example deep learning algorithm is DeSTIN, which is being integrated with OpenCog for perception processing. Defrosting: Restoring, into the RAM portion of an Atomspace, an Atom (or set ther
. Jonathan Mugan and Benjamin Kuipers. Towards the application of reinforcement learning to undirected developmental learning. International Conf. on Epigenetic Robotics, 2008. Ko9. Jonathan Mugan and Benjamin Kuipers. Autonomously learning an action hierarchy using a learned qualitative state representation. [JCAI-09
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