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{"title":"Real-Time Episodic Memory Construction for Optimal Action Selection in Cognitive Robotics","authors":"Deon de Jager, Yahya Zweiri, Dimitrios Makris","volume":157,"journal":"International Journal of Mechanical and Mechatronics Engineering","pagesStart":34,"pagesEnd":43,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10011020","abstract":"<p>The three most important components in the cognitive architecture for cognitive robotics is memory representation, memory recall, and action-selection performed by the executive. In this paper, action selection, performed by the executive, is defined as a memory quantification and optimization process. The methodology describes the real-time construction of episodic memory through semantic memory optimization. The optimization is performed by set-based particle swarm optimization, using an adaptive entropy memory quantification approach for fitness evaluation. The performance of the approach is experimentally evaluated by simulation, where a UAV is tasked with the collection and delivery of a medical package. The experiments show that the UAV dynamically uses the episodic memory to autonomously control its velocity, while successfully completing its mission.<\/p>\r\n","references":"S. Lewandowsky and S. Farrell, Computational Modeling in Cognition: Principles and Practice. Sage Publications Inc., 2011, p. 357.\r\n[2]\tJ. R. Anderson, The Architecture of Cognition. Harvard University Press, 1983, p. 345.\r\n[3]\tJ. E. Laird, The SOAR Cognitive Architecture. The MIT Press, 2012.\r\n[4]\tC. Eliasmith, How to Build a Brain (Oxford Series on Cognitive Models and Architecture). United States: Oxford University Press, 2013, p. 456.\r\n[5]\tD. J. Blower, Information Processing - The Maximum Entropy Principle. CreateSpace Independent Publishing Platform, 2013.\r\n[6]\tB. J. G. Baars, Nicole M., Fundamentals of Cognitive Neuroscience - A Beginner's Guide, Second ed. Academic Press - Elsevier, 2018.\r\n[7]\tJ. R. Anderson, D. Bothell, M. D. Byrne, S. Douglass, C. Lebiere, and Y. Qin, \"An integrated theory of the mind,\" Psychological Review, vol. 111, 4, pp. 1036-1060, 2004.\r\n[8]\tE. Tulving, \"How many memory systems are there,\" American Psychologist, vol. 40, pp. 385-398, 1985.\r\n[9]\tG. A. Radvansky, Human Memory, Third ed. Routledge, 2017.\r\n[10]\tR. Eberhart and J. Kennedy, \"A new optimizer using particle swarm theory,\" in Micro Machine and Human Science, 1995. MHS '95., Proceedings of the Sixth International Symposium on, 4-6 Oct 1995 1995, pp. 39-43, doi: 10.1109\/mhs.1995.494215. \r\n[11]\tC. Wei-Neng, Z. Jun, H. S. H. Chung, Z. Wen-Liang, W. Wei-gang, and S. Yu-Hui, \"A Novel Set-Based Particle Swarm Optimization Method for Discrete Optimization Problems,\" Evolutionary Computation, IEEE Transactions on, vol. 14, no. 2, pp. 278-300, 2010, doi: 10.1109\/tevc.2009.2030331.\r\n[12]\tJ. Langeveld and A. Engelbrecht, \"Set-based particle swarm optimization applied to the multidimensional knapsack problem,\" (in English), Swarm Intelligence, vol. 6, no. 4, pp. 297-342, 2012\/12\/01 2012, doi: 10.1007\/s11721-012-0073-4.\r\n[13]\tE. T. Jaynes, \"Information Theory and Statistical Mechanics,\" Physical Review, vol. 106, no. 4, pp. 620-630, 1957. (Online). Available: http:\/\/link.aps.org\/doi\/10.1103\/PhysRev.106.620.\r\n[14]\tC. E. Shannon, \"A mathematical theory of communication,\" Bell System Technical Journal, The, vol. 27, no. 4, pp. 623-656, 1948, doi: 10.1002\/j.1538-7305.1948.tb00917.x.\r\n[15]\tD. De Jager, \"UAV Benchmark mission 2,\" ed, 2019, p. Video of UAV Benchmark mission 2.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 157, 2020"}