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to learn procedures that will maxi- mize some Goal whose Truth Value is estimated via an expected reward calculation (where "reward" may mean simply the Truth Value of some Atom defined as "reward"). Goal-driven learning is more general than reinforcement learning as thus defined; and the learning that CogPrime does, which
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
to learn procedures that will maxi- mize some Goal whose Truth Value is estimated via an expected reward calculation (where "reward" may mean simply the Truth Value of some Atom defined as "reward"). Goal-driven learning is more general than reinforcement learning as thus defined; and the learning that CogPrime does, which
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
to learn procedures that will maxi- mize some Goal whose Truth Value is estimated via an expected reward calculation (where *reward” may mean simply the Truth Value of some Atom defined as ”reward”). Goal-driven learning is more general than reinforcement learning as thus defined; and the learning that CogPrime does, which is
. 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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