{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T10:47:07Z","timestamp":1761648427321},"reference-count":61,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2017,2,16]],"date-time":"2017-02-16T00:00:00Z","timestamp":1487203200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Fuzzy Syst."],"published-print":{"date-parts":[[2017,8]]},"DOI":"10.1007\/s40815-016-0284-8","type":"journal-article","created":{"date-parts":[[2017,2,16]],"date-time":"2017-02-16T07:59:55Z","timestamp":1487231995000},"page":"1058-1076","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["A Residual Gradient Fuzzy Reinforcement Learning Algorithm for Differential Games"],"prefix":"10.1007","volume":"19","author":[{"given":"Mostafa D.","family":"Awheda","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Howard M.","family":"Schwartz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,2,16]]},"reference":[{"key":"284_CR1","volume-title":"Fuzzy control","author":"KM Passino","year":"1998","unstructured":"Passino, K.M., Yurkovich, S.: Fuzzy control. Addison Wesley Longman, Inc., Menlo Park (1998)"},{"issue":"2","key":"284_CR2","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1002\/widm.1176","volume":"6","author":"N Marin","year":"2016","unstructured":"Marin, N., Ruiz, M.D., Sanchez, D.: Fuzzy frameworks for mining data associations: fuzzy association rules and beyond. Wiley Interdiscip. Rev.: Data Min. Knowl. Discov. 6(2), 50\u201369 (2016)","journal-title":"Wiley Interdiscip. Rev. Data Min. Knowl. Discov."},{"issue":"6","key":"284_CR3","doi-asserted-by":"crossref","first-page":"680","DOI":"10.1007\/BF02513367","volume":"37","author":"S Micera","year":"1999","unstructured":"Micera, S., Sabatini, A.M., Dario, P.: Adaptive fuzzy control of electrically stimulated muscles for arm movements. Med. Biol. Eng. Comput. 37(6), 680\u2013685 (1999)","journal-title":"Med. Biol. Eng. Comput."},{"issue":"5","key":"284_CR4","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1016\/j.enconman.2005.05.020","volume":"47","author":"F Daldaban","year":"2005","unstructured":"Daldaban, F., Ustkoyuncu, N., Guney, K.: Phase inductance estimation for switched reluctance motor using adaptive neuro- fuzzy inference system. Energy Convers. Manag. 47(5), 485\u2013493 (2005)","journal-title":"Energy Convers. Manag."},{"key":"284_CR5","volume-title":"Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence","author":"JSR Jang","year":"1997","unstructured":"Jang, J.S.R., Sun, C.T., Mizutani, E.: Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence. Prentice Hall, Upper Saddle River (1997)"},{"issue":"10","key":"284_CR6","doi-asserted-by":"crossref","first-page":"1126","DOI":"10.1016\/j.fss.2006.11.013","volume":"158","author":"S Labiod","year":"2007","unstructured":"Labiod, S., Guerra, T.M.: Adaptive fuzzy control of a class of SISO nonaffine nonlinear systems. Fuzzy Sets Syst. 158(10), 1126\u20131137 (2007)","journal-title":"Fuzzy Sets Syst."},{"issue":"2","key":"284_CR7","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.fss.2006.06.005","volume":"158","author":"HK Lam","year":"2007","unstructured":"Lam, H.K., Leung, F.H.F.: Fuzzy controller with stability and performance rules for nonlinear systems. Fuzzy Sets Syst. 158(2), 147\u2013163 (2007)","journal-title":"Fuzzy Sets Syst."},{"issue":"1","key":"284_CR8","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/S0165-0114(03)00116-7","volume":"141","author":"H Hagras","year":"2004","unstructured":"Hagras, H., Callaghan, V., Colley, M.: Learning and adaptation of an intelligent mobile robot navigator operating in unstructured environment based on a novel online Fuzzy-Genetic system. Fuzzy Sets Syst. 141(1), 107\u2013160 (2004)","journal-title":"Fuzzy Sets Syst."},{"issue":"2","key":"284_CR9","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1016\/j.asoc.2005.05.007","volume":"7","author":"M Mucientes","year":"2007","unstructured":"Mucientes, M., Moreno, D.L., Bugarn, A., Barro, S.: Design of a fuzzy controller in mobile robotics using genetic algorithms. Appl. Soft Comput. 7(2), 540\u2013546 (2007)","journal-title":"Appl. Soft Comput."},{"key":"284_CR10","volume-title":"A Course in Fuzzy Systems and Control","author":"LX Wang","year":"1997","unstructured":"Wang, L.X.: A Course in Fuzzy Systems and Control. Prentice Hall, Upper Saddle River (1997)"},{"key":"284_CR11","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.robot.2010.09.006","volume":"59","author":"SF Desouky","year":"2011","unstructured":"Desouky, S.F., Schwartz, H.M.: Self-learning fuzzy logic controllers for pursuit-evasion differential games. Robot. Auton. Syst. 59, 22\u201333 (2011)","journal-title":"Robot. Auton. Syst."},{"key":"284_CR12","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1109\/TSMC.1983.6313077","volume":"5","author":"AG Barto","year":"1983","unstructured":"Barto, A.G., Sutton, R.S., Anderson, C.W.: Neuronlike adaptive elements that can solve difficult learning control problems. IEEE Trans. Syst. Man Cybern. 5, 834\u2013846 (1983)","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"284_CR13","volume-title":"Reinforcement Learning: An Introduction, 1.1","author":"RS Sutton","year":"1998","unstructured":"Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction, 1.1. MIT press, Cambridge (1998)"},{"key":"284_CR14","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1613\/jair.301","volume":"4","author":"LP Kaelbling","year":"1996","unstructured":"Kaelbling, L.P., Littman, M.L., Moore, A.W.: Reinforcement learning: a survey. J. Artif. Intell. Res. 4, 237\u2013285 (1996)","journal-title":"J. Artif. Intell. Res."},{"key":"284_CR15","doi-asserted-by":"crossref","unstructured":"Awheda, M.D., Schwartz, H.M.: The residual gradient FACL algorithm for differential games. IN: IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE), pp. 1006\u20131011 (2015)","DOI":"10.1109\/CCECE.2015.7129412"},{"issue":"1","key":"284_CR16","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1109\/TFUZZ.2010.2081994","volume":"19","author":"W Hinojosa","year":"2011","unstructured":"Hinojosa, W., Nefti, S., Kaymak, U.: Systems control with generalized probabilistic fuzzy-reinforcement learning. IEEE Trans. Fuzzy Syst. 19(1), 51\u201364 (2011)","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"284_CR17","doi-asserted-by":"crossref","unstructured":"Rodr\u00edguez, M., Iglesias, R., Regueiro, C.V., Correa, J., Barro, S.: Autonomous and fast robot learning through motivation. In: Robotics and Autonomous Systems, vol. 55.9, pp. 735\u2013740. Elsevier (2007)","DOI":"10.1016\/j.robot.2007.05.005"},{"key":"284_CR18","doi-asserted-by":"crossref","DOI":"10.1002\/9781118884614","volume-title":"Multi-agent machine learning: a reinforcement approach","author":"HM Schwartz","year":"2014","unstructured":"Schwartz, H.M.: Multi-agent machine learning: a reinforcement approach. Wiley, New York (2014)"},{"issue":"1","key":"284_CR19","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1007\/s10846-015-0315-y","volume":"83","author":"MD Awheda","year":"2016","unstructured":"Awheda, M.D., Schwartz, H.M.: A decentralized fuzzy learning algorithm for pursuit-evasion differential games with superior evaders. J. Intell. Robot. Syst. 83(1), 35\u201353 (2016)","journal-title":"J. Intell. Robot. Syst."},{"key":"284_CR20","unstructured":"Awheda, M.D., Schwartz, H.M.: A fuzzy learning algorithm for multi-player pursuit-evasion differential games with superior evaders. In: Proceedings of the 2016 IEEE International Systems Conference, Orlando, Florida (2016)"},{"key":"284_CR21","doi-asserted-by":"crossref","unstructured":"Awheda, M.D., Schwartz, H.M.: A fuzzy reinforcement learning algorithm using a predictor for pursuit-evasion games. In: Proceedings of the 2016 IEEE International Systems Conference, Orlando, Florida (2016)","DOI":"10.1109\/SYSCON.2016.7490542"},{"key":"284_CR22","doi-asserted-by":"crossref","unstructured":"Smart, W.D., Kaelbling, L.P.: Effective reinforcement learning for mobile robots. In: IEEE International Conference on Robotics and Automation, Proceedings ICRA\u201902, 4 (2002)","DOI":"10.1109\/ROBOT.2002.1014237"},{"issue":"1","key":"284_CR23","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1109\/TSMCB.2003.808179","volume":"33","author":"C Ye","year":"2003","unstructured":"Ye, C., Yung, N.H.C., Wang, D.: A fuzzy controller with supervised learning assisted reinforcement learning algorithm for obstacle avoidance. IEEE Trans. Syst. Man Cybern. Part B: Cybern. 33(1), 17\u201327 (2003)","journal-title":"IEEE Trans. Syst. Man Cybern. Part B: Cybern."},{"key":"284_CR24","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.robot.2003.11.006","volume":"46","author":"T Kondo","year":"2004","unstructured":"Kondo, T., Ito, K.: A reinforcement learning with revolutionary state recruitment strategy for autonomous mobile robots control. Robot. Auton. Syst. 46, 111\u2013124 (2004)","journal-title":"Robot. Auton. Syst."},{"issue":"1","key":"284_CR25","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1162\/106454604322875913","volume":"10","author":"DA Gutnisky","year":"2004","unstructured":"Gutnisky, D.A., Zanutto, B.S.: Learning obstacle avoidance with an operant behavior model. Artif. Life 10(1), 65\u201381 (2004)","journal-title":"Artif. Life"},{"issue":"3","key":"284_CR26","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1109\/TITS.2005.853698","volume":"6","author":"X Dai","year":"2005","unstructured":"Dai, X., Li, C., Rad, A.B.: An approach to tune fuzzy controllers based on reinforcement learning for autonomous vehicle control. IEEE Trans. Intell. Transp. Syst. 6(3), 285\u2013293 (2005)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"284_CR27","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1109\/TCYB.2014.2319577","volume":"45.1","author":"B Luo","year":"2015","unstructured":"Luo, B., Wu, H.N., Huang, T.: Off-policy reinforcement learning for $$H_{\\infty }$$ H \u221e control design. IEEE Trans. Cybern. 45.1, 65\u201376 (2015)","journal-title":"IEEE Trans. Cybern."},{"key":"284_CR28","doi-asserted-by":"crossref","first-page":"684","DOI":"10.1109\/TNNLS.2014.2320744","volume":"26.4","author":"B Luo","year":"2015","unstructured":"Luo, B., Wu, H.N., Li, H.X.: Adaptive optimal control of highly dissipative nonlinear spatially distributed processes with neuro-dynamic programming. IEEE Trans. Neural Netw. Learn. Syst. 26.4, 684\u2013696 (2015)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"284_CR29","doi-asserted-by":"crossref","unstructured":"Luo, B., Wu, H.N., Huang, T., Liu, D.: Reinforcement learning solution for HJB equation arising in constrained optimal control problem. In: Neural Networks, vol. 71, pp. 150\u2013158. Elsevier (2015)","DOI":"10.1016\/j.neunet.2015.08.007"},{"key":"284_CR30","doi-asserted-by":"crossref","unstructured":"Modares, H., Lewis, F.L., Naghibi-Sistani, M.B.: Integral reinforcement learning and experience replay for adaptive optimal control of partially-unknown constrained-input continuous-time systems. In: Automatica, vol. 50.1, pp. 193\u2013202. Elsevier (2014)","DOI":"10.1016\/j.automatica.2013.09.043"},{"key":"284_CR31","doi-asserted-by":"crossref","first-page":"1048","DOI":"10.2514\/1.G000173","volume":"37.3","author":"W Dixon","year":"2014","unstructured":"Dixon, W.: Optimal adaptive control and differential games by reinforcement learning principles, J. Guid. Control Dyn. 37.3, 1048\u20131049 (2014)","journal-title":"J. Guid. Control Dyn."},{"key":"284_CR32","doi-asserted-by":"crossref","first-page":"8106","DOI":"10.1021\/ie4031743","volume":"53.19","author":"B Luo","year":"2014","unstructured":"Luo, B., Wu, H.N., Li, H.X.: Data-based suboptimal neuro-control design with reinforcement learning for dissipative spatially distributed processes, Ind. Eng. Chem. Res. 53.19, 8106\u20138119 (2014)","journal-title":"Ind. Eng. Chem. Res."},{"key":"284_CR33","first-page":"1884","volume":"23.12","author":"HN Wu","year":"2012","unstructured":"Wu, H.N., Luo, B.: Neural network based online simultaneous policy update algorithm for solving the HJI equation in nonlinear control. IEEE Trans. Neural Netw. Learn. Syst. 23.12, 1884\u20131895 (2012)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"12","key":"284_CR34","doi-asserted-by":"crossref","first-page":"1331","DOI":"10.1049\/iet-cta.2015.0669","volume":"10","author":"Z Xia","year":"2016","unstructured":"Xia, Z., Zhao, D.: Online reinforcement learning control by Bayesian inference. IET Control Theory Appl. 10(12), 1331\u20131338 (2016)","journal-title":"IET Control Theory Appl."},{"issue":"1","key":"284_CR35","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1109\/TFUZZ.2015.2418000","volume":"24","author":"YJ Liu","year":"2016","unstructured":"Liu, Y.J., Gao, Y., Tong, S., Li, Y.: Fuzzy approximation-based adaptive backstepping optimal control for a class of nonlinear discrete-time systems with dead-zone. IEEE Trans. Fuzzy Syst. 24(1), 16\u201328 (2016)","journal-title":"IEEE Trans. Fuzzy Syst."},{"issue":"12","key":"284_CR36","doi-asserted-by":"crossref","first-page":"1339","DOI":"10.1049\/iet-cta.2015.0769","volume":"10","author":"Y Zhu","year":"2016","unstructured":"Zhu, Y., Zhao, D., Li, X.: Using reinforcement learning techniques to solve continuous-time non-linear optimal tracking problem without system dynamics. IET Control Theory Appl. 10(12), 1339\u20131347 (2016)","journal-title":"IET Control Theory Appl."},{"key":"284_CR37","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.automatica.2015.10.039","volume":"64","author":"R Kamalapurkar","year":"2016","unstructured":"Kamalapurkar, R., Walters, P., Dixon, W.E.: Model-based reinforcement learning for approximate optimal regulation. Automatica 64, 94\u2013104 (2016)","journal-title":"Automatica"},{"key":"284_CR38","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.neucom.2016.02.029","volume":"194","author":"H Jiang","year":"2016","unstructured":"Jiang, H., Zhang, H., Luo, Y., Wang, J.: Optimal tracking control for completely unknown nonlinear discrete-time Markov jump systems using data-based reinforcement learning method. Neurocomputing 194, 176\u2013182 (2016)","journal-title":"Neurocomputing"},{"issue":"1","key":"284_CR39","first-page":"9","volume":"3","author":"RS Sutton","year":"1988","unstructured":"Sutton, R.S.: Learning to predict by the methods of temporal differences. Mach. Learn. 3(1), 9\u201344 (1988)","journal-title":"Mach. Learn."},{"key":"284_CR40","first-page":"295","volume":"14","author":"P Dayan","year":"1994","unstructured":"Dayan, P., Sejnowski, T.J.: TD( $$\\lambda$$ \u03bb ) converges with probability 1. Mach. Learn. 14, 295\u2013301 (1994)","journal-title":"Mach. Learn."},{"issue":"3\u20134","key":"284_CR41","first-page":"341","volume":"8","author":"P Dayan","year":"1992","unstructured":"Dayan, P.: The convergence of TD( $$\\lambda$$ \u03bb ) for general $$\\lambda$$ \u03bb . Mach. Learn. 8(3\u20134), 341\u2013362 (1992)","journal-title":"Mach. Learn."},{"key":"284_CR42","doi-asserted-by":"crossref","first-page":"1185","DOI":"10.1162\/neco.1994.6.6.1185","volume":"6","author":"T Jakkola","year":"1993","unstructured":"Jakkola, T., Jordan, M., Singh, S.: On the convergence of stochastic iterative dynamic programming. Neural Comput. 6, 1185\u20131201 (1993)","journal-title":"Neural Comput."},{"key":"284_CR43","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1109\/5326.704563","volume":"28.3","author":"L Jouffe","year":"1998","unstructured":"Jouffe, L.: Fuzzy inference system learning by reinforcement methods. IEEE Trans. Syst. Man Cybern. C 28.3, 338\u2013355 (1998)","journal-title":"IEEE Trans. Syst. Man Cybern. C"},{"issue":"10","key":"284_CR44","doi-asserted-by":"crossref","first-page":"1420","DOI":"10.1016\/j.fss.2008.11.026","volume":"160","author":"A Bonarini","year":"2009","unstructured":"Bonarini, A., Lazaric, A., Montrone, F., Restelli, M.: Reinforcement distribution in fuzzy Q-learning. Fuzzy Sets Syst. 160(10), 1420\u20131443 (2009)","journal-title":"Fuzzy Sets Syst."},{"issue":"10","key":"284_CR45","doi-asserted-by":"crossref","first-page":"910","DOI":"10.1002\/acs.1249","volume":"25","author":"SF Desouky","year":"2011","unstructured":"Desouky, S.F., Schwartz, H.M.: Q ( $$\\lambda$$ \u03bb )-learning adaptive fuzzy logic controllers for pursuit\u2013evasion differential games. Int. J. Adapt. Control Signal Process. 25(10), 910\u2013927 (2011)","journal-title":"Int. J. Adapt. Control Signal Process."},{"key":"284_CR46","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s10846-009-9380-4","volume":"59","author":"SN Givigi Jr","year":"2010","unstructured":"Givigi Jr., S.N., Schwartz, H.M., Lu, X.: A reinforcement learning adaptive fuzzy controller for differential games. J. Intell. Robot. Syst. 59, 3\u201330 (2010)","journal-title":"J. Intell. Robot. Syst."},{"issue":"18","key":"284_CR47","doi-asserted-by":"crossref","first-page":"3764","DOI":"10.1016\/j.ins.2007.03.012","volume":"177","author":"XS Wang","year":"2007","unstructured":"Wang, X.S., Cheng, Y.H., Yi, J.Q.: A fuzzy Actor\u2013Critic reinforcement learning network. Inf. Sci. 177(18), 3764\u20133781 (2007)","journal-title":"Inf. Sci."},{"key":"284_CR48","doi-asserted-by":"crossref","unstructured":"Baird, L.: Residual algorithms: reinforcement learning with function approximation. In: ICML, pp. 30\u201337 (1995)","DOI":"10.1016\/B978-1-55860-377-6.50013-X"},{"key":"284_CR49","unstructured":"Boyan, J., Moore, A.W.: Generalization in reinforcement learning: safely approximating the value function. In: Advances in Neural Information Processing Systems, vol. 7, pp. 369\u2013376. Cambridge, MA, The MIT Press (1995)"},{"key":"284_CR50","unstructured":"Gordon, G.J.: Reinforcement learning with function approximation converges to a region. In: Advances in Neural Information Processing Systems, vol. 13, pp. 1040\u20131046. MIT Press (2001)"},{"key":"284_CR51","unstructured":"Schoknecht, R., Merke, A.: TD(0) converges provably faster than the residual gradient algorithm. In: ICML (2003)"},{"issue":"5","key":"284_CR52","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1109\/9.580874","volume":"42","author":"JN Tsitsiklis","year":"1997","unstructured":"Tsitsiklis, J.N., Roy, B.V.: An analysis of temporal-difference learning with function approximation. IEEE Trans. Autom. Control 42(5), 674\u2013690 (1997)","journal-title":"IEEE Trans. Autom. Control"},{"issue":"2","key":"284_CR53","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/S0004-3702(02)00121-2","volume":"136","author":"M Bowling","year":"2002","unstructured":"Bowling, M., Veloso, M.: Multiagent learning using a variable learning rate. Artif. Intell. 136(2), 215\u2013250 (2002)","journal-title":"Artif. Intell."},{"issue":"2","key":"284_CR54","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1109\/91.669012","volume":"6","author":"WM Buijtenen Van","year":"1998","unstructured":"Van Buijtenen, W.M., Schram, G., Babuska, R., Verbruggen, H.B.: Adaptive fuzzy control of satellite attitude by reinforcement learning. IEEE Trans. Fuzzy Syst. 6(2), 185\u2013194 (1998)","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"284_CR55","first-page":"113","volume":"7.1","author":"EH Mamdani","year":"1975","unstructured":"Mamdani, E.H., Assilian, S.: An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Man Mach. Stud. 7.1, 113 (1975)","journal-title":"Int. J. Man Mach. Stud."},{"issue":"1","key":"284_CR56","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1109\/TSMC.1985.6313399","volume":"15","author":"T Takagi","year":"1985","unstructured":"Takagi, T., Sugeno, M.: Fuzzy identification of systems and its applications to modelling and control. IEEE Trans. Syst. Man Cybern. SMC 15(1), 116\u2013132 (1985)","journal-title":"IEEE Trans. Syst. Man Cybern. SMC"},{"key":"284_CR57","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/0165-0114(88)90113-3","volume":"28","author":"M Sugeno","year":"1988","unstructured":"Sugeno, M., Kang, G.: Structure identification of fuzzy model. Fuzzy Sets Syst. 28, 15\u201333 (1988)","journal-title":"Fuzzy Sets Syst."},{"key":"284_CR58","volume-title":"Differential Games","author":"R Isaacs","year":"1965","unstructured":"Isaacs, R.: Differential Games. Wiley, New York (1965)"},{"key":"284_CR59","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511546877","volume-title":"Planning Algorithms","author":"SM LaValle","year":"2006","unstructured":"LaValle, S.M.: Planning Algorithms. Cambridge University Press, Cambridge (2006)"},{"key":"284_CR60","unstructured":"Lim, S.H., Furukawa, T., Dissanayake, G., Whyte, H.F.D.: A time-optimal control strategy for pursuit-evasion games problems, In: International Conference on Robotics and Automation, New Orleans, LA (2004)"},{"key":"284_CR61","doi-asserted-by":"crossref","unstructured":"Desouky, S.F., Schwartz, H.M.: Different hybrid intelligent systems applied for the pursuit\u2013evasion game. In: 2009 IEEE International Conference on Systems, Man, and Cybernetics, pp. 2677\u20132682 (2009)","DOI":"10.1109\/ICSMC.2009.5346113"}],"container-title":["International Journal of Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s40815-016-0284-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s40815-016-0284-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s40815-016-0284-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,22]],"date-time":"2024-06-22T14:15:33Z","timestamp":1719065733000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s40815-016-0284-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,2,16]]},"references-count":61,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2017,8]]}},"alternative-id":["284"],"URL":"https:\/\/doi.org\/10.1007\/s40815-016-0284-8","relation":{},"ISSN":["1562-2479","2199-3211"],"issn-type":[{"value":"1562-2479","type":"print"},{"value":"2199-3211","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,2,16]]}}}