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Perspective on Development. MIT Press, 1997. Ede93. Gerald Edelman. Neural darwinism: Selection and reentrant signaling in higher brain function. Neuron, 10, 1993. PF92. Christian Freksa and Robert Milton. Temporal reasoning based on semi-intervals. Artificial Intel- ligence, 54(1-2):199 - 227, 1992
nd seem relevant to AGI, especially advanced AGI systems capable of strong self-modification. • PLN: short for Probabilistic Logic Networks • PLN, First-Order: See First-Order hnference • PLN, Higher-Order: See Higher-Order Inference • PLN Rules: A PLN Rule takes as input one or more Atoms (the "premises"
Press, 1997. EFTA00624120 References 345 Ede93. Gerald Edelman. Neural darwinism: Selection and reentrant signaling in higher brain function. Neuron, 10, 1993. Elm91. J. Elman. Distributed representations, simple recurrent networks, and grammatical structure. Machine Learning, 7:195-226, 1991.
nd seem relevant to AGI, especially advanced AGI systems capable of strong self-modification. • PLN: short for Probabilistic Logic Networks • PLN, First-Order: See First-Order hnference • PLN, Higher-Order: See Higher-Order Inference • PLN Rules: A PLN Rule takes as input one or more Atoms (the "premises"
, 1997. HOUSE_OVERSIGHT_013260 References 345 Ede93. Gerald Edelman. Neural darwinism: Selection and reentrant signaling in higher brain function. Neuron, 10, 1993. Elm91. J. Elman. Distributed representations, simple recurrent networks, and grammatical structure. Machine Learning, 7:195-226, 1991. E
et and seem relevant to AGI, especially advanced AGI systems capable of strong self-modification. PLN: short for Probabilistic Logic Networks PLN, First-Order: See First-Order Inference PLN, Higher-Order: See Higher-Order Inference PLN Rules: A PLN Rule takes as input one or more Atoms (the “premises”, us
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