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EFTA00624128_sub_006 - EFTA00624128_555

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ial Intel- ligence, 54(1-2):199 - 227, 1992. PLI2. Jeremy Fishel and Gerald Loeb. Bayesian exploration for intelligent identification of textures. Frontiers in Neurorobotics 6-4, 2012. Pri98. Roy. FYieden. Physics from Fisher Information. Cambridge U. Press, 1998. PT02. G. Pauconnier and M. Turner. Th

s, or observe the consequences of various hypothetical situations. Particularly important for dealing with episodic knowledge. • Interval Algebra: Allen Interval Algebra, a mathematical theory of the relationships be- tween time intervals. CogPrime utilizes a fuzzified version of classic Interval Algebra. • IRC Learn

EFTA00623759_sub_004 - EFTA00623759_369

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-14, 1995. HC08. David Hart and Ben Goertzel. Opencog: A software framework for integrative artificial general intelligence. In ACI, volume 171 of Frontiers in Artificial Intelligence and Applications. pages 468-472. IOS Press, 2008. HHPO12. Adam Hampshire, Roger Highfield, Beth Parkin, and Adrian Owen

HOUSE_OVERSIGHT_012899_sub_004 - HOUSE_OVERSIGHT_013267

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I-14, 1995. HGO8. David Hart and Ben Goertzel. Opencog: A software framework for integrative artificial general intelligence. In AGI, volume 171 of Frontiers in Artificial Intelligence and Applications, pages 468-472. IOS Press, 2008. HHPO12. Adam Hampshire, Roger Highfield, Beth Parkin, and Adrian Owen.

ces, or observe the consequences of various hypothetical situations. Particularly important for dealing with episodic knowledge. e Interval Algebra: Allen Interval Algebra, a mathematical theory of the relationships be- tween time intervals. CogPrime utilizes a fuzzified version of classic Interval Algebra. e IRC Learn