{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T07:36:54Z","timestamp":1743147414999,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030613761"},{"type":"electronic","value":"9783030613778"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-61377-8_26","type":"book-chapter","created":{"date-parts":[[2020,10,15]],"date-time":"2020-10-15T19:04:06Z","timestamp":1602788646000},"page":"371-386","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Improving FIFA Player Agents Decision-Making Architectures Based on Convolutional Neural Networks Through Evolutionary Techniques"],"prefix":"10.1007","author":[{"given":"Matheus Prado Prandini","family":"Faria","sequence":"first","affiliation":[]},{"given":"Rita Maria Silva","family":"Julia","sequence":"additional","affiliation":[]},{"given":"L\u00eddia Bononi Paiva","family":"Tomaz","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,10,13]]},"reference":[{"key":"26_CR1","unstructured":"Baker, B., Gupta, O., Naik, N., Raskar, R.: Designing neural network architectures using reinforcement learning. In: 5th International Conference on Learning Representations (2017)"},{"key":"26_CR2","doi-asserted-by":"crossref","unstructured":"Buche, C., Even, C., Soler, J.: Autonomous virtual player in a video game imitating human players: the orion framework. In: 2018 International Conference on Cyberworlds, pp. 108\u2013113 (2018)","DOI":"10.1109\/CW.2018.00029"},{"key":"26_CR3","volume-title":"A Dictionary of Psychology","author":"AM Coleman","year":"2009","unstructured":"Coleman, A.M.: A Dictionary of Psychology, 3rd edn. Oxford University Press, Oxford (2009)","edition":"3"},{"key":"26_CR4","unstructured":"Faria, M.P.P., Julia, R.M.S., Tomaz, L.B.P.: Evaluating the performance of the deep active imitation learning algorithm in the dynamic environment of FIFA player agents. In: 18th IEEE International Conference on Machine Learning and Applications (2019)"},{"key":"26_CR5","unstructured":"Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. MIT Press, New York (2016). http:\/\/www.deeplearningbook.org"},{"key":"26_CR6","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: The IEEE Conference on Computer Vision and Pattern Recognition (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"26_CR7","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1007\/s00521-017-3241-z","volume":"29","author":"A Hussein","year":"2018","unstructured":"Hussein, A., Elyan, E., Gaber, M.M., Jayne, C.: Deep imitation learning for 3D navigation tasks. Neural Comput. Appl. 29, 389\u2013404 (2018)","journal-title":"Neural Comput. Appl."},{"key":"26_CR8","doi-asserted-by":"publisher","first-page":"21:1","DOI":"10.1145\/3054912","volume":"50","author":"A Hussein","year":"2017","unstructured":"Hussein, A., Gaber, M.M., Elyan, E., Jayne, C.: Imitation learning: a survey of learning methods. ACM Comput. Surv. 50, 21:1\u201321:35 (2017)","journal-title":"ACM Comput. Surv."},{"key":"26_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TG.2019.2896986","volume":"12","author":"N Justesen","year":"2020","unstructured":"Justesen, N., Bontrager, P., Togelius, J., Risi, S.: Deep learning for video game playing. IEEE Trans. Games 12, 1\u201320 (2020)","journal-title":"IEEE Trans. Games"},{"key":"26_CR10","unstructured":"Krizhevsky, A., Nair, V., Hinton, G.: CIFAR-10 and CIFAR-100 (Canadian institute for advanced research). http:\/\/www.cs.toronto.edu\/~kriz\/cifar.html"},{"key":"26_CR11","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. In: Pereira, F., Burges, C.J.C., Bottou, L., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems 25, pp. 1097\u20131105. Curran Associates, Inc. (2012)"},{"key":"26_CR12","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.E.: Deep learning. Nature 521, 436\u2013444 (2015)","journal-title":"Nature"},{"key":"26_CR13","unstructured":"Liu, H., Simonyan, K., Vinyals, O., Fernando, C., Kavukcuoglu, K.: Hierarchical representations for efficient architecture search (2018)"},{"key":"26_CR14","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.neucom.2016.12.038","volume":"234","author":"W Liu","year":"2017","unstructured":"Liu, W., Wang, Z., Liu, X., Zeng, N., Liu, Y., Alsaadi, F.E.: A survey of deep neural network architectures and their applications. Neurocomputing 234, 11\u201326 (2017)","journal-title":"Neurocomputing"},{"key":"26_CR15","doi-asserted-by":"crossref","unstructured":"Liu, Y., Gupta, A., Abbeel, P., Levine, S.: Imitation from observation: learning to imitate behaviors from raw video via context translation. In: 2018 IEEE International Conference on Robotics and Automation, pp. 1118\u20131125 (2018)","DOI":"10.1109\/ICRA.2018.8462901"},{"key":"26_CR16","first-page":"193","volume":"9","author":"BL Miller","year":"1995","unstructured":"Miller, B.L., Miller, B.L., Goldberg, D.E., Goldberg, D.E.: Genetic algorithms, tournament selection, and the effects of noise. Complex Syst. 9, 193\u2013212 (1995)","journal-title":"Complex Syst."},{"key":"26_CR17","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, A.A.: Human-level control through deep reinforcement learning. Nature 518, 529\u2013533 (2015)","journal-title":"Nature"},{"key":"26_CR18","unstructured":"Real, E., et al.: Large-scale evolution of image classifiers. In: Proceedings of the 34th International Conference on Machine Learning, Vol. 70, pp. 2902\u20132911 (2017)"},{"key":"26_CR19","doi-asserted-by":"publisher","unstructured":"Refaeilzadeh, P., Tang, L., Liu, H.: Cross-validation. In: Liu, L., \u00d6zsu, M.T. (eds.) Encyclopedia of Database Systems, pp. 532\u2013538. Springer, Boston (2009). https:\/\/doi.org\/10.1007\/978-0-387-39940-9","DOI":"10.1007\/978-0-387-39940-9"},{"key":"26_CR20","volume-title":"Artificial Intelligence: A Modern Approach","author":"S Russell","year":"2009","unstructured":"Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach, 3rd edn. Prentice Hall Press, Upper Saddle River (2009)","edition":"3"},{"key":"26_CR21","doi-asserted-by":"publisher","unstructured":"Sammut, C., Webb, G.I.: Holdout evaluation. In: Encyclopedia of Machine Learning, pp. 506\u2013507. Springer, Boston (2010). https:\/\/doi.org\/10.1007\/978-0-387-30164-8_369","DOI":"10.1007\/978-0-387-30164-8_369"},{"key":"26_CR22","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1109\/2.294849","volume":"27","author":"M Srinivas","year":"1994","unstructured":"Srinivas, M., Patnaik, L.M.: Genetic algorithms: a survey. Computer 27, 17\u201326 (1994)","journal-title":"Computer"},{"issue":"9","key":"26_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TCYB.2020.2983860","volume":"50","author":"Y Sun","year":"2020","unstructured":"Sun, Y., Xue, B., Zhang, M., Yen, G.G., Lv, J.: Automatically designing CNN architectures using the genetic algorithm for image classification. IEEE Trans. Cybern. 50(9), 1\u201315 (2020)","journal-title":"IEEE Trans. Cybern."},{"key":"26_CR24","doi-asserted-by":"crossref","unstructured":"Xie, L., Yuille, A.: Genetic CNN. In: 2017 IEEE International Conference on Computer Vision, pp. 1388\u20131397 (2017)","DOI":"10.1109\/ICCV.2017.154"},{"key":"26_CR25","unstructured":"Zoph, B., Le, Q.V.: Neural architecture search with reinforcement learning. In: International Conference on Learning Representations (2017)"}],"container-title":["Lecture Notes in Computer Science","Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-61377-8_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,12]],"date-time":"2020-11-12T09:57:13Z","timestamp":1605175033000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-61377-8_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030613761","9783030613778"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-61377-8_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"13 October 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BRACIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Brazilian Conference on Intelligent Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Rio Grande","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Brazil","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":"20 October 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 October 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bracis2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www2.sbc.org.br\/bracis2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"JEMS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"228","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"91","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"40% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3,5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to the Corona pandemic BRACIS 2020 was held as a virtual event.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}