{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T23:23:28Z","timestamp":1768519408755,"version":"3.49.0"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2020,3,6]],"date-time":"2020-03-06T00:00:00Z","timestamp":1583452800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,3,6]],"date-time":"2020-03-06T00:00:00Z","timestamp":1583452800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cogn Comput"],"published-print":{"date-parts":[[2021,5]]},"DOI":"10.1007\/s12559-020-09716-6","type":"journal-article","created":{"date-parts":[[2020,3,6]],"date-time":"2020-03-06T11:03:02Z","timestamp":1583492582000},"page":"612-625","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["SOAR Improved Artificial Neural Network for Multistep Decision-making Tasks"],"prefix":"10.1007","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7624-4728","authenticated-orcid":false,"given":"Guoyu","family":"Zuo","sequence":"first","affiliation":[]},{"given":"Tingting","family":"Pan","sequence":"additional","affiliation":[]},{"given":"Tielin","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yang","family":"Yang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,3,6]]},"reference":[{"key":"9716_CR1","unstructured":"Kotseruba I, Tsotsos JK. 40 years of cognitive architectures: core cognitive abilities and practical applications. Artif Intell Rev;40:1\u201378."},{"issue":"4","key":"9716_CR2","doi-asserted-by":"publisher","first-page":"1036","DOI":"10.1037\/0033-295X.111.4.1036","volume":"111","author":"JR Anderson","year":"2004","unstructured":"Anderson JR, Bothell D, Byrne MD, Douglass S, Lebiere C, Qin Y. An integrated theory of the mind. Psychol Rev 2004;111(4):1036.","journal-title":"Psychol Rev"},{"issue":"3","key":"9716_CR3","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1207\/s15516709cog0000_22","volume":"29","author":"JR Anderson","year":"2005","unstructured":"Anderson JR. Human symbol manipulation within an integrated cognitive architecture. Cogn Sci 2005;29(3): 313\u2013341.","journal-title":"Cogn Sci"},{"issue":"1","key":"9716_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/0004-3702(87)90050-6","volume":"33","author":"JE Laird","year":"1987","unstructured":"Laird JE, Newell A, Rosenbloom PS. Soar: an architecture for general intelligence. Artif Intell 1987;33 (1):1\u201364.","journal-title":"Artif Intell"},{"key":"9716_CR5","doi-asserted-by":"crossref","unstructured":"Laird JE. 2012. The Soar cognitive architecture. MIT Press, Cambridge.","DOI":"10.7551\/mitpress\/7688.001.0001"},{"issue":"4","key":"9716_CR6","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1016\/S1364-6613(99)01294-2","volume":"3","author":"RM French","year":"1999","unstructured":"French RM. Catastrophic forgetting in connectionist networks. Trends Cogn Sci 1999;3(4):128\u2013135.","journal-title":"Trends Cogn Sci"},{"key":"9716_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.conb.2013.09.009","volume":"25","author":"C Eliasmith","year":"2014","unstructured":"Eliasmith C, Trujillo O. The use and abuse of large-scale brain models. Curr Opinion Neurobiol 2014;25: 1\u20136.","journal-title":"Curr Opinion Neurobiol"},{"key":"9716_CR8","first-page":"23","volume":"10","author":"J Hawkins","year":"2016","unstructured":"Hawkins J, Ahmad S. Why neurons have thousands of synapses, a theory of sequence memory in neocortex. Front Neural Circ 2016;10:23.","journal-title":"Front Neural Circ"},{"issue":"1","key":"9716_CR9","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1023\/A:1008332731824","volume":"11","author":"R Sun","year":"1999","unstructured":"Sun R, Peterson T, Merrill E. A hybrid architecture for situated learning of reactive sequential decision making. Appl Intell 1999;11(1):109\u2013127.","journal-title":"Appl Intell"},{"key":"9716_CR10","doi-asserted-by":"publisher","first-page":"124","DOI":"10.3389\/fpsyg.2013.00124","volume":"4","author":"RC O\u2019Reilly","year":"2013","unstructured":"O\u2019Reilly RC, Wyatte D, Herd S, Mingus B, Jilk DJ. Recurrent processing during object recognition. Front Psychol 2013;4:124.","journal-title":"Front Psychol"},{"key":"9716_CR11","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.neunet.2014.09.003","volume":"61","author":"J Schmidhuber","year":"2015","unstructured":"Schmidhuber J. Deep learning in neural networks: an overview. Neural Netw 2015;61:85\u2013117.","journal-title":"Neural Netw"},{"key":"9716_CR12","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J. Delving deep into rectifiers: surpassing human-level performance on imagenet classification. Proceedings of the IEEE international conference on computer vision; 2015. p. 1026\u20131034.","DOI":"10.1109\/ICCV.2015.123"},{"key":"9716_CR13","doi-asserted-by":"publisher","first-page":"1231","DOI":"10.1016\/j.neucom.2017.09.061","volume":"275","author":"Z Wang","year":"2018","unstructured":"Wang Z, Wang X, Wang G. Learning fine-grained features via a cnn tree for large-scale classification. Neurocomputing 2018;275:1231\u20131240.","journal-title":"Neurocomputing"},{"issue":"1","key":"9716_CR14","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1109\/TASL.2011.2134090","volume":"20","author":"GE Dahl","year":"2012","unstructured":"Dahl GE, Yu D, Li D, Acero A. Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition. IEEE Trans Audio Speech Lang Process 2012;20(1):30\u201342.","journal-title":"IEEE Trans Audio Speech Lang Process"},{"key":"9716_CR15","doi-asserted-by":"crossref","unstructured":"Redmon J, Divvala S, Girshick R, Farhadi A. You only once: look Unified, real-time object detection. Proceedings of the IEEE conference on computer vision and pattern recognition; 2016. p. 779\u2013788.","DOI":"10.1109\/CVPR.2016.91"},{"key":"9716_CR16","doi-asserted-by":"crossref","unstructured":"Maturana D, Scherer S. Voxnet: a 3d convolutional neural network for real-time object recognition. 2015 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE; 2015. p. 922\u2013928.","DOI":"10.1109\/IROS.2015.7353481"},{"key":"9716_CR17","unstructured":"Oh J, Guo X, Lee H, Lewis RL, Singh S. Action-conditional video prediction using deep networks in atari games. In: Advances in neural information processing systems; 2015. p. 2863\u20132871."},{"issue":"11","key":"9716_CR18","doi-asserted-by":"publisher","first-page":"2083","DOI":"10.1109\/TASLP.2018.2851664","volume":"26","author":"G Weisz","year":"2018","unstructured":"Weisz G, Budzianowski P, Su P-H, Gasic M. Sample efficient deep reinforcement learning for dialogue systems with large action spaces. IEEE\/ACM Trans Audio Speech Lang Process (TASLP) 2018;26(11):2083\u20132097.","journal-title":"IEEE\/ACM Trans Audio Speech Lang Process (TASLP)"},{"key":"9716_CR19","doi-asserted-by":"crossref","unstructured":"Zen H, Sak H. 2015. Unidirectional long short-term memory recurrent neural network with recurrent output layer for low-latency speech synthesis. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE; 2015. P. 4470\u20134474.","DOI":"10.1109\/ICASSP.2015.7178816"},{"key":"9716_CR20","doi-asserted-by":"crossref","unstructured":"Finn C, Levine S. 2017. Deep visual foresight for planning robot motion. In: IEEE International Conference on Robotics and Automation (ICRA). IEEE; 2017. p. 2786\u20132793.","DOI":"10.1109\/ICRA.2017.7989324"},{"issue":"7540","key":"9716_CR21","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1038\/nature14236","volume":"518","author":"V Mnih","year":"2015","unstructured":"Mnih V, Kavukcuoglu K, Silver D, Rusu AA, Veness J, Bellemare MG, Graves Ax, Riedmiller M, Fidjeland AK, Ostrovski G, et al. Human-level control through deep reinforcement learning. Nature 2015;518(7540):529.","journal-title":"Nature"},{"key":"9716_CR22","doi-asserted-by":"crossref","unstructured":"Ge L, Ren Z, Li Y, Xue Z, Wang Y, Cai J, Yuan J. 3d hand shape and pose estimation from a single rgb image. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition; 2019. p. 10833\u201310842.","DOI":"10.1109\/CVPR.2019.01109"},{"key":"9716_CR23","doi-asserted-by":"crossref","unstructured":"Dong J, Jiang W, Huang Q, Bao H, Zhou X. Fast and robust multi-person 3d pose estimation from multiple views. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition; 2019. p. 7792\u20137801.","DOI":"10.1109\/CVPR.2019.00798"},{"key":"9716_CR24","unstructured":"Huajun Z, Jin Z, Rui W, Tan M. Multi-objective reinforcement learning algorithm and its application in drive system. In 2008 34th Annual Conference of IEEE Industrial Electronics. IEEE; 2008. p. 274\u2013279."},{"key":"9716_CR25","doi-asserted-by":"crossref","unstructured":"Hester T, Vecerik M, Pietquin O, Lanctot M, Piot B, Horgan D, Quan J, Sendonaris A, Osband I, et al. Deep q-learning from demonstrations. In: Thirty-Second AAAI Conference on Artificial Intelligence; 2018.","DOI":"10.1609\/aaai.v32i1.11757"},{"key":"9716_CR26","doi-asserted-by":"crossref","unstructured":"Ellefsen KO, Torresen J. Self-adapting goals allow transfer of predictive models to new tasks; 2019.","DOI":"10.1007\/978-3-030-35664-4_3"},{"issue":"7587","key":"9716_CR27","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1038\/nature16961","volume":"529","author":"D Silver","year":"2016","unstructured":"Silver D, Huang A, Maddison CJ, Guez A, Sifre L, Van den Driessche G, Schrittwieser J, Antonoglou I, Panneershelvam V, Lanctot M. Mastering the game of go with deep neural networks and tree search. Nature 2016;529(7587):484\u2013489.","journal-title":"Nature"},{"key":"9716_CR28","doi-asserted-by":"crossref","unstructured":"Yang Y, Yi L, Fermuller C, Aloimonos Y. Robot learning manipulation action plans by \u201cwatching\u201d unconstrained videos from the world wide web. In: Twenty-ninth Aaai Conference on Artificial Intelligence; 2015.","DOI":"10.1609\/aaai.v29i1.9671"},{"issue":"7540","key":"9716_CR29","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1038\/nature14236","volume":"518","author":"M Volodymyr","year":"2015","unstructured":"Volodymyr M, Koray K, David S, Rusu AA, Joel Vx, Bellemare MG, Alex G, Martin R, Fidjeland AK, Georg O. Human-level control through deep reinforcement learning. Nature 2015;518(7540): 529.","journal-title":"Nature"},{"key":"9716_CR30","doi-asserted-by":"crossref","unstructured":"Zhang H, Lan X, Zhou X, Tian Z, Zhang Y, Zheng N. 2018. Visual manipulation relationship network for autonomous robotics. In: IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids). IEEE; 2018. p. 118\u2013125.","DOI":"10.1109\/HUMANOIDS.2018.8625071"},{"key":"9716_CR31","doi-asserted-by":"crossref","unstructured":"Zeng A, Song S, Lee J, Rodriguez A, Funkhouser T. 2019. Tossingbot: learning to throw arbitrary objects with residual physics.","DOI":"10.15607\/RSS.2019.XV.004"},{"issue":"5","key":"9716_CR32","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1007\/s11633-018-1139-6","volume":"15","author":"H-Z Chen","year":"2018","unstructured":"Chen H-Z, Tian G-H, Liu G-L. A selective attention guided initiative semantic cognition algorithm for service robot. Int J Autom Comput 2018;15(5):559\u2013569.","journal-title":"Int J Autom Comput"},{"issue":"1","key":"9716_CR33","doi-asserted-by":"publisher","first-page":"55","DOI":"10.7746\/jkros.2017.12.1.055","volume":"12","author":"C Van Dang","year":"2017","unstructured":"Van Dang C, Pham TX, Gil K-J, Shin Y-B, Kim J-W, et al. Implementation of a refusable human-robot interaction task with humanoid robot by connecting soar and ros. J Korea Robot Soc 2017;12(1):55\u201364.","journal-title":"J Korea Robot Soc"},{"issue":"2","key":"9716_CR34","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1080\/09540091.2014.968093","volume":"27","author":"J-Y Puigbo","year":"2015","unstructured":"Puigbo J-Y, Pumarola A, Angulo C, Tellez R. Using a cognitive architecture for general purpose service robot control. Connect Sci 2015;27(2):105\u2013117.","journal-title":"Connect Sci"},{"issue":"2","key":"9716_CR35","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1007\/s12559-018-9621-6","volume":"11","author":"J Zheng","year":"2019","unstructured":"Zheng J, Cai F, Chen W, Feng C, Chen H. Hierarchical neural representation for document classification. Cogn Comput 2019;11(2):317\u2013327.","journal-title":"Cogn Comput"},{"key":"9716_CR36","doi-asserted-by":"crossref","unstructured":"Zhou K, Wei R, Xu Z, Zhang Q, Lu H, Zhang G. 2019. An air combat decision learning system based on a brain-like cognitive mechanism. Cognitive Computation.","DOI":"10.1007\/s12559-019-09683-7"},{"issue":"1","key":"9716_CR37","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1007\/s12559-018-9597-2","volume":"11","author":"P Liu","year":"2019","unstructured":"Liu P, Qin X. A new decision-making method based on interval-valued linguistic intuitionistic fuzzy information. Cogn Comput 2019;11(1):125\u2013144.","journal-title":"Cogn Comput"},{"key":"9716_CR38","doi-asserted-by":"crossref","unstructured":"Doumanoglou A, Kouskouridas R, Malassiotis S, Kim T-K. Recovering 6d object pose and predicting next-best-view in the crowd. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition; 2016. p. 3583\u20133592.","DOI":"10.1109\/CVPR.2016.390"},{"key":"9716_CR39","doi-asserted-by":"crossref","unstructured":"Hodan T, Michel F, Brachmann E, Kehl W, GlentBuch A, Kraft D, Drost B, Vidal J, Ihrke S, Zabulis X, et al. Bop: benchmark for 6d object pose estimation. In: Proceedings of the European Conference on Computer Vision (ECCV); 2018. p. 19\u201334.","DOI":"10.1007\/978-3-030-01249-6_2"},{"key":"9716_CR40","doi-asserted-by":"crossref","unstructured":"Hinterstoisser S, Lepetit V, Ilic S, Holzer S, Bradski G, Konolige K, Navab N. Model based training, detection and pose estimation of texture-less 3d objects in heavily cluttered scenes. In: Asian conference on computer vision. Springer; 2012. p. 548\u2013562.","DOI":"10.1007\/978-3-642-37331-2_42"},{"key":"9716_CR41","doi-asserted-by":"crossref","unstructured":"Hinterstoisser S, Holzer S, Cagniart C, Ilic S, Konolige K, Navab N, Lepetit V. Multimodal templates for real-time detection of texture-less objects in heavily cluttered scenes. In: IEEE International Conference on Computer Vision; 2012.","DOI":"10.1109\/ICCV.2011.6126326"},{"issue":"1","key":"9716_CR42","first-page":"3221","volume":"15","author":"L Van Der Maaten","year":"2014","unstructured":"Van Der Maaten L. Accelerating t-sne using tree-based algorithms. J Mach Learn Res 2014;15(1):3221\u20133245.","journal-title":"J Mach Learn Res"},{"key":"9716_CR43","first-page":"2579","volume":"9","author":"L van der Maaten","year":"2008","unstructured":"van der Maaten L, Hinton G. Visualizing data using t-sne. J Mach Learn Res 2008;9:2579\u20132605.","journal-title":"J Mach Learn Res"}],"container-title":["Cognitive Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-020-09716-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12559-020-09716-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-020-09716-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T20:58:51Z","timestamp":1666040331000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12559-020-09716-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,6]]},"references-count":43,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021,5]]}},"alternative-id":["9716"],"URL":"https:\/\/doi.org\/10.1007\/s12559-020-09716-6","relation":{},"ISSN":["1866-9956","1866-9964"],"issn-type":[{"value":"1866-9956","type":"print"},{"value":"1866-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,6]]},"assertion":[{"value":"6 June 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 February 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 March 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with Ethical Standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of Interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}}]}}