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y different yet both appear cognitively necessary. The argument for using probability in an AGI system is assailed by some AGI researchers such as Pei Wang, but we are swayed by the theoretical arguments in favor of probability theory's mathematically fundamental nature, as well as the massive demonstra
nandez M., and Mackie I. Efficient reductions with director strings. Evolutionary Computation, 1997. SMK12. Jeremy Stober, Risto Miikkulainen, and Benjamin Kuipers. Learning geometry from sensorimo- tor experience. In Proceedings of the First Joint Conference on Development and Learning and Epigenetic Robotics,
achines. Oxford University Press, 2010. Wan95. P. Wang. Non-Axiomatic Reasoning System. PhD Thesis, Indiana University. Bloomington, 1995. Wan06. Pei Wang. Rigid Flexibility: The Logic of Intelligence. Springer. 2006. Was09. Mark Weser. Ethics for self-improving machines. In ACf-09, 2009. http://vimeo
rd, 2004. Min88. Marvin Minsky. The Society of Mind. MIT Press. 1988. Min07. Marvin Minsky. The Emotion Machine. 2007. MK07. Joseph Modayil and Benjamin Kuipers. Autonomous development of a grounded object ontology by a learning robot. AAAI-07, 2007. MK08. Jonathan Mugan and Benjamin Kuipers. Towards the a
Machines. Oxford University Press, 2010. Wan95. P. Wang. Non-Aziomatic Reasoning System. PhD Thesis, Indiana University. Bloomington, 1995. Wan06. Pei Wang. Rigid Flexibility: The Logic of Intelligence. Springer, 2006. Was09. Mark Waser. Ethics for self-improving machines. In AGI-09, 2009. http: //vimeo
e. Bradford, 2004. in88. Marvin Minsky. The Society of Mind. MIT Press, 1988. inO7. Marvin Minsky. The Emotion Machine. 2007. KO7. Joseph Modayil and Benjamin Kuipers. Autonomous development of a grounded object ontology by a learning robot. AAAI-07, 2007. KO08. Jonathan Mugan and Benjamin Kuipers. Towards the appl
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