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m's memory of what it's useful to pay attention to, in what contexts. In CogPrime this is managed by the attention allocation subsystem. • Backward Chainer: A piece of software, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. • CIM-Dynamic: Concretely-Implemented Mind D
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
m's memory of what it's useful to pay attention to, in what contexts. In CogPrime this is managed by the attention allocation subsystem. • Backward Chainer: A piece of software, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. • CIM-Dynamic: Concretely-Implemented Mind D
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
stem’s memory of what it’s useful to pay attention to, in what contexts. In CogPrime this is managed by the attention allocation subsystem. Backward Chainer: A piece of software, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. CIM-Dynamic: Concretely-Implemented Mind Dyn
. 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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