{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T04:34:16Z","timestamp":1769920456061,"version":"3.49.0"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030653507","type":"print"},{"value":"9783030653514","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-65351-4_29","type":"book-chapter","created":{"date-parts":[[2021,1,4]],"date-time":"2021-01-04T22:03:06Z","timestamp":1609797786000},"page":"361-371","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Deep Reinforcement Learning for Control of Probabilistic Boolean Networks"],"prefix":"10.1007","author":[{"given":"Georgios","family":"Papagiannis","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sotiris","family":"Moschoyiannis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,1,5]]},"reference":[{"issue":"1","key":"29_CR1","first-page":"337","volume":"5","author":"A Acernese","year":"2021","unstructured":"Acernese, A., Yerudkar, A., Glielmo, L., Vecchio, C.D.: Reinforcement learning approach to feedback stabilization problem of probabilistic Boolean control networks. IEEE Control Syst. Lett. 5(1), 337\u2013342 (2021)","journal-title":"IEEE Control Syst. Lett."},{"issue":"1","key":"29_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/S0022-5193(03)00035-3","volume":"223","author":"R Albert","year":"2003","unstructured":"Albert, R., Othmer, H.G.: The topology of the regulatory interactions predicts the expression pattern of the segment polarity genes in Drosophila melanogaster. J. Theor. Biol. 223(1), 1\u201318 (2003)","journal-title":"J. Theor. Biol."},{"key":"29_CR3","volume-title":"Dynamic Programming","author":"R Bellman","year":"1957","unstructured":"Bellman, R.: Dynamic Programming. Princeton University Press, Princeton (1957)"},{"key":"29_CR4","doi-asserted-by":"crossref","unstructured":"Bittner, M., Meltzer, P., Chen, Y., et, al.: Molecular classification of cutaneous malignant melanoma by gene expression profiling. Nature 406(6795), 536\u2013540 (2000)","DOI":"10.1038\/35020115"},{"key":"29_CR5","doi-asserted-by":"crossref","unstructured":"Choo, S.M., Ban, B., Joo, J., Cho, K.H.: The phenotype control kernel of a biomolecular regulatory network. BMC Systems Biology 12(19) (2018)","DOI":"10.1186\/s12918-018-0576-8"},{"key":"29_CR6","doi-asserted-by":"publisher","first-page":"1942","DOI":"10.1038\/ncomms2939","volume":"4","author":"SP Cornelius","year":"2013","unstructured":"Cornelius, S.P., Kath, W.L., Motter, A.E.: Realistic control of network dynamics. Nature Commun. 4, 1942 (2013)","journal-title":"Nature Commun."},{"issue":"1","key":"29_CR7","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1109\/MSP.2007.273057","volume":"24","author":"A Datta","year":"2007","unstructured":"Datta, A., Pal, R., Choudhary, A., Dougherty, E.: Control approaches for probabilistic gene regulatory networks - what approaches have been developed for addressing the issue of intervention? IEEE Signal Process. Mag. 24(1), 54\u201363 (2007)","journal-title":"IEEE Signal Process. Mag."},{"issue":"1\u20132","key":"29_CR8","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1023\/A:1023909812213","volume":"52","author":"A Datta","year":"2003","unstructured":"Datta, A., Choudhary, A., Bittner, M.L., Dougherty, E.R.: External control in Markovian genetic regulatory networks. Mach. Learn. 52(1\u20132), 169\u2013191 (2003)","journal-title":"Mach. Learn."},{"key":"29_CR9","doi-asserted-by":"crossref","unstructured":"Faryabi, B., Datta, A., Dougherty, E.R.: On reinforcement learning in genetic regulatory networks. In: IEEE\/SP 14th Workshop on Statistical Signal Processing, pp. 11\u201315 (2007)","DOI":"10.1109\/SSP.2007.4301208"},{"issue":"5415","key":"29_CR10","first-page":"1","volume":"5","author":"J Gao","year":"2014","unstructured":"Gao, J., Liu, Y.Y., D\u2019Sousa, R., Barabasi, A.L.: Target control of complex networks. Nat. Commun. 5(5415), 1\u201318 (2014)","journal-title":"Nat. Commun."},{"key":"29_CR11","unstructured":"Hasselt, H.v., Guez, A., Silver, D.: Deep reinforcement learning with double q-learning. In: Proc. of the Thirtieth AAAI Conference on Artificial Intelligence, pp. 2094\u20132100. AAAI Press (2016)"},{"issue":"6","key":"29_CR12","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1007\/s001099900023","volume":"77","author":"S Huang","year":"1999","unstructured":"Huang, S.: Gene expression profiling, genetic networks, and cellular states: an integrating concept for tumorigenesis and drug discovery. J. Mol. Med. 77(6), 469\u2013480 (1999)","journal-title":"J. Mol. Med."},{"issue":"1","key":"29_CR13","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1006\/excr.2000.5044","volume":"261","author":"S Huang","year":"2000","unstructured":"Huang, S., Ingber, D.: Shape-dependent control of cell growth, differentiation, and apoptosis: switching between attractors in cell regulatory networks. Exp. Cell Res. 261(1), 91\u2013103 (2000)","journal-title":"Exp. Cell Res."},{"issue":"1","key":"29_CR14","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1007\/s41109-018-0088-x","volume":"3","author":"MR Karlsen","year":"2018","unstructured":"Karlsen, M.R., Moschoyiannis, S.: Evolution of control with learning classifier systems. Appl. Netw. Sci. 3(1), 30 (2018)","journal-title":"Appl. Netw. Sci."},{"issue":"1","key":"29_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s41109-019-0243-z","volume":"4","author":"MR Karlsen","year":"2019","unstructured":"Karlsen, M.R., Moschoyiannis, S.: Learning versus optimal intervention in random Boolean networks. Appl. Netw. Sci. 4(1), 1\u201329 (2019)","journal-title":"Appl. Netw. Sci."},{"key":"29_CR16","doi-asserted-by":"publisher","first-page":"2223","DOI":"10.1038\/srep02223","volume":"3","author":"J Kim","year":"2013","unstructured":"Kim, J., Park, S.M., Cho, K.H.: Discovery of a kernel for controlling biomolecular regulatory networks. Sci. Rep. 3, 2223 (2013)","journal-title":"Sci. Rep."},{"issue":"8","key":"29_CR17","doi-asserted-by":"publisher","first-page":"1966","DOI":"10.1109\/TNNLS.2016.2572063","volume":"28","author":"K Kobayashi","year":"2017","unstructured":"Kobayashi, K., Hiraishi, K.: Design of probabilistic Boolean networks based on network structure and steady-state probabilities. IEEE Trans. Neural Netw. Learn. Syst. 28(8), 1966\u20131971 (2017)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"29_CR18","doi-asserted-by":"publisher","first-page":"1297","DOI":"10.1016\/j.physa.2018.09.104","volume":"503","author":"Q Liu","year":"2018","unstructured":"Liu, Q., He, Y., Wang, J.: Optimal control for probabilistic Boolean networks using discrete-time Markov decision processes. Phys. A 503, 1297\u20131307 (2018)","journal-title":"Phys. A"},{"issue":"7346","key":"29_CR19","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1038\/nature10011","volume":"473","author":"YY Liu","year":"2011","unstructured":"Liu, Y.Y., Slotine, J.J., Barab\u00e1si, A.L.: Controllability of complex networks. Nature 473(7346), 167 (2011)","journal-title":"Nature"},{"issue":"3","key":"29_CR20","doi-asserted-by":"publisher","first-page":"e55946","DOI":"10.1371\/journal.pone.0055946","volume":"8","author":"M Marques-Pita","year":"2013","unstructured":"Marques-Pita, M., Rocha, L.M.: Canalization and control in automata networks: body segmentation in drosophila melanogaster. PLoS ONE 8(3), e55946 (2013)","journal-title":"PLoS ONE"},{"issue":"7540","key":"29_CR21","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1038\/nature14236","volume":"518","author":"V Mnih","year":"2015","unstructured":"Mnih, V., et al.: Human-level control through deep reinforcement learning. Nature 518(7540), 529\u2013533 (2015)","journal-title":"Nature"},{"key":"29_CR22","doi-asserted-by":"crossref","unstructured":"Moschoyiannis, S., Elia, N., Penn, A., Lloyd, D.J.B., Knight, C.: A web-based tool for identifying strategic intervention points in complex systems. In: Proceedings of Games for the Synthesis of Complex Systems (CASSTING @ ETAPS). EPTCS, vol. 220, pp. 39\u201352 (2016)","DOI":"10.4204\/EPTCS.220.4"},{"key":"29_CR23","doi-asserted-by":"publisher","first-page":"2375","DOI":"10.1109\/TSP.2006.873740","volume":"54","author":"R Pal","year":"2006","unstructured":"Pal, R., Datta, A., Dougherty, E.: Optimal infinite horizon control for probabilistic Boolean networks. IEEE Trans. Signal Process. 54, 2375\u20132387 (2006)","journal-title":"IEEE Trans. Signal Process."},{"key":"29_CR24","doi-asserted-by":"crossref","unstructured":"Papagiannis, G., Moschoyiannis, S.: Learning to control random Boolean networks: A deep reinforcement learning approach. In: Complex Networks 2019. Studies in Computational Intelligence, vol. 881, pp. 721\u2013734. Springer, Cham (2019)","DOI":"10.1007\/978-3-030-36687-2_60"},{"key":"29_CR25","unstructured":"Schaul, T., Quan, J., I., A., Silver, D.: Prioritized experience replay. In: International Conference on Learning Representations (ICLR) (2016)"},{"issue":"10","key":"29_CR26","doi-asserted-by":"publisher","first-page":"1319","DOI":"10.1093\/bioinformatics\/18.10.1319","volume":"18","author":"I Shmulevich","year":"2002","unstructured":"Shmulevich, I., Dougherty, E., Zhang, W.: Gene perturbation and intervention in probabilistic Boolean networks. Bioinformatics 18(10), 1319\u20131331 (2002)","journal-title":"Bioinformatics"},{"issue":"2","key":"29_CR27","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1093\/bioinformatics\/18.2.261","volume":"18","author":"I Shmulevich","year":"2002","unstructured":"Shmulevich, I., Dougherty, E.R., Kim, S., Zhang, W.: Probabilistic Boolean networks: a rule-based uncertainty model for gene regulatory networks. Bioinformatics 18(2), 261\u2013274 (2002)","journal-title":"Bioinformatics"},{"key":"29_CR28","unstructured":"Sirin, U., Polat, F., Alhajj, R.: Employing batch reinforcement learning to control gene regulation without explicitly constructing gene regulatory networks. In: 23rd International Joint Conference on Artificial Intelligence (IJCAI), pp. 2042\u20132048 (2013)"},{"key":"29_CR29","unstructured":"Sootla, A., Strelkowa, N., Ernst, D., Barahona, M., Stan, G.: Toggling a genetic switch using reinforcement learning. In: 9th French Meeting on Planning, Decision Making and Learning (2014)"},{"issue":"6","key":"29_CR30","doi-asserted-by":"publisher","first-page":"2202","DOI":"10.1109\/TNNLS.2019.2927241","volume":"31","author":"M Toyoda","year":"2020","unstructured":"Toyoda, M., Wu, Y.: On optimal time-varying feedback controllability for probabilistic Boolean control networks. IEEE Trans. Neural Netw. Learn. Syst. 31(6), 2202\u20132208 (2020)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"29_CR31","first-page":"2613","volume":"23","author":"H van Hasselt","year":"2010","unstructured":"van Hasselt, H.: Double Q-learning. Adv. Neural Inf. Process. Syst. 23, 2613\u20132621 (2010)","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"29_CR32","unstructured":"Velarde, C., et\u00a0al.: Boolean networks: a study on microarray data discretization. In: XIV XIV Congreso Espa\u00f1ol sobre Tecnologias y L\u00f3gica fuzzy (ESTYLF) Cuencas Mineras (Mieres-Langreo),pp. 17\u201319 (2008)"},{"issue":"5","key":"29_CR33","doi-asserted-by":"publisher","first-page":"2031","DOI":"10.1109\/TNNLS.2017.2661863","volume":"29","author":"Y Wu","year":"2019","unstructured":"Wu, Y., Shen, T.: Policy iteration algorithm for optimal control of stochastic logical dynamical systems. IEEE Trans. Neural Netw. Learn. Syst. 29(5), 2031\u20132036 (2019)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."}],"container-title":["Studies in Computational Intelligence","Complex Networks & Their Applications IX"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-65351-4_29","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,1,5]],"date-time":"2021-01-05T07:05:12Z","timestamp":1609830312000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-65351-4_29"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030653507","9783030653514"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-65351-4_29","relation":{},"ISSN":["1860-949X","1860-9503"],"issn-type":[{"value":"1860-949X","type":"print"},{"value":"1860-9503","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"5 January 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"COMPLEX NETWORKS 2020","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Complex Networks and Their Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Madrid","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 December 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 December 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iwcna2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.complexnetworks.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}