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Accelerating progress in Artificial General Intelligence: Choosing a benchmark for natural world interaction

Challenge Proposals for Cognitive Systems. Technical report, The MITRE Corporation. Version 1.5, Prepared for DARPA IPTO Brachman, R. J. 2006. (AA)AI more than the sum of its parts. AI Magazine 27(4):19-34. Carpenter, R., and Freeman, J. 2005. Computing machinery and the individual: The Personal Turing Test. Technical report, Jabberwacky. Cohen, P. R. 2005. If not Turing

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The Action Execution Process Implemented in Different Cognitive Architectures: A Review

References ACT-R 6.0 Tutorial. 2012. Unpublished manuscript. Retrieved from Albus, J. S., and Barbera, A. J. 2005. RCS: A cognitive architecture for intelligent multi-agent systems. Annual Reviews in Control, 29(1):87-99. Anderson, J. 2007. How can the human mind occur in the physical universe? : Oxford University Press. Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., and Qin, Y. 2004. An integrated

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Modelling Dynamic Decision Making with the ACT-R Cognitive Architecture

References Anderson, J. R.; Bothell, D.; Byrne, M. D.; Douglass, S.; Lebiere, C.; and Qin, Y. 2004. An integrated theory of the mind. Psychological Review 111:1036-1060. Anderson, J. A. 2007. How can the Human Mind Occur in the Physical Universe? New York, NY: Oxford University Press. Anzai, Y. 1984. Cognitive control of real-time event driven systems. Cognitive Science 8:221-254. Besnard, D.; Greathead, D.; and Baxter, G. 2004. When mental model's go

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Artificial General Intelligence: Concept, State of the Art, and Future Prospects

.; Schlesinger, M.; et al. 2012. Mapping the landscape of human-level artificial general intelligence. AI Magazine 33(1):25-42. Albus, J. S. 2001. Engineering of mind: An introduction to the science of intelligent systems. Wiley. Alvarado, N.; Adams, S. S.; Burbeck, S.; and Latta, C. 2002. Beyond the Turing test: Performance metrics for evaluating a computer simulation of the human mind. In The 2nd International Conference on Development and Learning, 147-152. IEEE. Anderson, J. R., and Lebiere, C. 2003. The Newell test for a

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Validating Computational Cognitive Process Models across Multiple Timescales

References Anderson, J. R. (2002). Spanning seven orders of magnitude: a challenge for cognitive modeling. Cognitive Science, 26 , 85-112. Anderson, J. R. (2007). How Can the Human Mind Occur in the Physical Universe? Oxford: Oxford University Press. Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., & Qin, Y. (2004). An Integrated Theory of the Mind. Psychological Review, 111 (4), 1036-1060. Anderson, J. R., & Lebiere, C. (2003

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Cognitive Architectures and Autonomy: A Comparative Review

References Anderson, J. R. 1996. ACT: A simple theory of complex cognition. American Psychologist . 51: 355-365. Anderson, J. R., Matessa, M., Lebiere, C. 1997. ACT-R: A theory of higher level cognition and its relation to visual attention. Human-Computer Interaction . 12: 439-462. Anderson, J. R., Lebiere, C. 2003. The Newell test for a theory of cognition. Behavioral and brain Sciences . 26: 587-601. Anderson, J. R., John, B. E., Just, M. A., Carpenter

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Causal Mathematical Logic as a guiding framework for the prediction of “Intelligence Signals” in brain simulations

.A.; and Smith, S.S. 2001.Using brain MERMER testing to detect knowledge despite efforts to conceal. J Forensic Sci. 46 (1): 135-143. Fiebelkorn, I.C.; Snyder, A.C.; and et al. 2013. Cortical cross-frequency coupling predicts perceptual outcomes. Neuroimage. 1;69:126-37. Fleury, V. 2011. A change in boundary conditions induces a discontinuity of tissue flow in chicken embryos and the formation of the cephalic fold. The European Physical Journal E. 34(7) Freeman, W. J.; and Kozma, R. 2010. Freeman's mass action Scholarpedia, 5(1):8040 Available

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Universes and simulations: Civilizational development in nested embedding

References [1] Barrow J. D. Living in a simulated universe. In Carr B., editor, Universe of Multiverse?, pages 481-486. 2007. [2] Basl J. The ethics of creating artificial consciousness. APA Newsletter on Philosophy and Computers, 13(1):25-30, 2013. [3] Beane S. R., Davoudi Z., and Savage M. J. Constraints on the universe as a numerical simulation. The European Physical Journal A, 50(9):1-9, 2014. [4] Bedau M. A. Artificial life: organization, adaptation and complexity from the bottom up. Trends

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Classifier Ensembles Using Structural Features For Spammer Detection In Online Social Networks

social engineering attacks, Journal of Information Security and Applications , 2014, 1-10. [24] Lam Ho-Y., Yeung Dit-Y., A Learning approach to spam detection based on social networks, in: Proceedings of the 4 th Conference on Email and Anti-Spam (CEAS) , Mountain View, California, 2007. [25] Lancichinetti A., Fortunato S., Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities, Physical Review E , 80, 2009. [26] Mislove A., Marcon M., Gummadi K. P., Druschel P., Bhattacharjee B

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Diagnostic System for Induction Motor Stator Winding Faults Based on Axial Flux


The article presents the results of research on the use of an axial flux in the diagnostics of induction motor stator winding fed by a frequency converter. Voltage signal waveforms proportional to the axial flux were recorded during motor operation under various conditions and were analyzed with regard to the detection of stator winding short circuits. The taps of the selected coil turns of stator phases were introduced into the tested motor, which allowed to physical modelling inter-turn short circuits. The structure and operation of the computer system used to monitor the state of induction motor windings were discussed. The developed diagnostic system was made in the National Instruments LabVIEW environment. The analysis of faults of the axial flux was made in the detection of induction motor stator winding. The results of experimental research conducted using the developed diagnostic system have also been presented.

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