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  • Source: [Anais]: CTD 2020. Conference titles: Concurso de Teses e Dissertações da SBC. Unidade: EP

    Subjects: APRENDIZADO COMPUTACIONAL, SISTEMAS MULTIAGENTES

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      SILVA, Felipe Leno da e REALI COSTA, Anna Helena. Methods and algorithms for knowledge reuse in multiagent reinforcement learning. 2020, Anais.. Porto Alegre: Sociedade Brasileira de Computação, 2020. Disponível em: https://doi.org/10.5753/ctd.2020.11360. Acesso em: 24 abr. 2026.
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      Silva, F. L. da, & Reali Costa, A. H. (2020). Methods and algorithms for knowledge reuse in multiagent reinforcement learning. In [Anais]: CTD 2020. Porto Alegre: Sociedade Brasileira de Computação. doi:10.5753/ctd.2020.11360
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      Silva FL da, Reali Costa AH. Methods and algorithms for knowledge reuse in multiagent reinforcement learning [Internet]. [Anais]: CTD 2020. 2020 ;[citado 2026 abr. 24 ] Available from: https://doi.org/10.5753/ctd.2020.11360
    • Vancouver

      Silva FL da, Reali Costa AH. Methods and algorithms for knowledge reuse in multiagent reinforcement learning [Internet]. [Anais]: CTD 2020. 2020 ;[citado 2026 abr. 24 ] Available from: https://doi.org/10.5753/ctd.2020.11360
  • Unidade: EP

    Subjects: INTELIGÊNCIA ARTIFICIAL, SISTEMAS MULTIAGENTES

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      SILVA, Felipe Leno da. Methods and algorithms for knowledge reuse in multiagent reinforcement learning. 2019. Tese (Doutorado) – Universidade de São Paulo, São Paulo, 2019. Disponível em: https://teses.usp.br/teses/disponiveis/3/3141/tde-21112019-113201/. Acesso em: 24 abr. 2026.
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      Silva, F. L. da. (2019). Methods and algorithms for knowledge reuse in multiagent reinforcement learning (Tese (Doutorado). Universidade de São Paulo, São Paulo. Recuperado de https://teses.usp.br/teses/disponiveis/3/3141/tde-21112019-113201/
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      Silva FL da. Methods and algorithms for knowledge reuse in multiagent reinforcement learning [Internet]. 2019 ;[citado 2026 abr. 24 ] Available from: https://teses.usp.br/teses/disponiveis/3/3141/tde-21112019-113201/
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      Silva FL da. Methods and algorithms for knowledge reuse in multiagent reinforcement learning [Internet]. 2019 ;[citado 2026 abr. 24 ] Available from: https://teses.usp.br/teses/disponiveis/3/3141/tde-21112019-113201/
  • Source: Journal of Artificial Intelligence Research. Unidade: EP

    Assunto: APRENDIZADO COMPUTACIONAL

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      SILVA, Felipe Leno da e REALI COSTA, Anna Helena. A Survey on Transfer Learning for Multiagent Reinforcement Learning Systems. Journal of Artificial Intelligence Research, v. 64, p. 645-703, 2019Tradução . . Disponível em: https://doi.org/10.1613/jair.1.11396. Acesso em: 24 abr. 2026.
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      Silva, F. L. da, & Reali Costa, A. H. (2019). A Survey on Transfer Learning for Multiagent Reinforcement Learning Systems. Journal of Artificial Intelligence Research, 64, 645-703. doi:10.1613/jair.1.11396
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      Silva FL da, Reali Costa AH. A Survey on Transfer Learning for Multiagent Reinforcement Learning Systems [Internet]. Journal of Artificial Intelligence Research. 2019 ; 64 645-703.[citado 2026 abr. 24 ] Available from: https://doi.org/10.1613/jair.1.11396
    • Vancouver

      Silva FL da, Reali Costa AH. A Survey on Transfer Learning for Multiagent Reinforcement Learning Systems [Internet]. Journal of Artificial Intelligence Research. 2019 ; 64 645-703.[citado 2026 abr. 24 ] Available from: https://doi.org/10.1613/jair.1.11396
  • Source: IEEE Transactions on Cybernetics. Unidade: EP

    Assunto: APRENDIZADO COMPUTACIONAL

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      SILVA, Felipe Leno da e REALI COSTA, Anna Helena e GLATT, Ruben. MOO-MDP: an Object-Oriented Representation for Cooperative Multiagent Reinforcement Learning. IEEE Transactions on Cybernetics, v. 49 , n. 2, p. 567-579, 2019Tradução . . Disponível em: https://doi.org/10.1109/TCYB.2017.2781130. Acesso em: 24 abr. 2026.
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      Silva, F. L. da, Reali Costa, A. H., & Glatt, R. (2019). MOO-MDP: an Object-Oriented Representation for Cooperative Multiagent Reinforcement Learning. IEEE Transactions on Cybernetics, 49 ( 2), 567-579. doi:10.1109/TCYB.2017.2781130
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      Silva FL da, Reali Costa AH, Glatt R. MOO-MDP: an Object-Oriented Representation for Cooperative Multiagent Reinforcement Learning [Internet]. IEEE Transactions on Cybernetics. 2019 ; 49 ( 2): 567-579.[citado 2026 abr. 24 ] Available from: https://doi.org/10.1109/TCYB.2017.2781130
    • Vancouver

      Silva FL da, Reali Costa AH, Glatt R. MOO-MDP: an Object-Oriented Representation for Cooperative Multiagent Reinforcement Learning [Internet]. IEEE Transactions on Cybernetics. 2019 ; 49 ( 2): 567-579.[citado 2026 abr. 24 ] Available from: https://doi.org/10.1109/TCYB.2017.2781130
  • Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems (BRACIS). Unidade: EP

    Subjects: APRENDIZADO COMPUTACIONAL, ALGORITMOS, AGENTES INTELIGENTES, JOGOS

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      SILVA, Felipe Leno da e REALI COSTA, Anna Helena e STONE, Peter. Building self-play curricula online by playing with expert agents in adversarial games. 2019, Anais.. Piscataway: Escola Politécnica, Universidade de São Paulo, 2019. Disponível em: https://doi.org/10.1109/BRACIS.2019.00090. Acesso em: 24 abr. 2026.
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      Silva, F. L. da, Reali Costa, A. H., & Stone, P. (2019). Building self-play curricula online by playing with expert agents in adversarial games. In Proceedings. Piscataway: Escola Politécnica, Universidade de São Paulo. doi:10.1109/BRACIS.2019.00090
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      Silva FL da, Reali Costa AH, Stone P. Building self-play curricula online by playing with expert agents in adversarial games [Internet]. Proceedings. 2019 ;[citado 2026 abr. 24 ] Available from: https://doi.org/10.1109/BRACIS.2019.00090
    • Vancouver

      Silva FL da, Reali Costa AH, Stone P. Building self-play curricula online by playing with expert agents in adversarial games [Internet]. Proceedings. 2019 ;[citado 2026 abr. 24 ] Available from: https://doi.org/10.1109/BRACIS.2019.00090
  • Source: Conference paper at AAMAS 2019. Conference titles: International Conference on Autonomous Agents and Multiagent Systems. Unidade: EP

    Subjects: APRENDIZAGEM PROFUNDA, SISTEMAS MULTIAGENTES, TRANSFERÊNCIA (APRENDIZAGEM)

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      SILVA, Felipe Leno da e REALI COSTA, Anna Helena e STONE, Peter. Distributional reinforcement learning applied to robot soccer simulation. 2019, Anais.. [S.l.]: IFAAMAS, 2019. Disponível em: https://repositorio.usp.br/directbitstream/700e5786-bb0b-4a56-9a0a-f31ed12bab47/Distributional-Reinforcement-Learning-Applied-to-Robot-Soccer-Simulation.pdf. Acesso em: 24 abr. 2026.
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      Silva, F. L. da, Reali Costa, A. H., & Stone, P. (2019). Distributional reinforcement learning applied to robot soccer simulation. In Conference paper at AAMAS 2019. [S.l.]: IFAAMAS. Recuperado de https://repositorio.usp.br/directbitstream/700e5786-bb0b-4a56-9a0a-f31ed12bab47/Distributional-Reinforcement-Learning-Applied-to-Robot-Soccer-Simulation.pdf
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      Silva FL da, Reali Costa AH, Stone P. Distributional reinforcement learning applied to robot soccer simulation [Internet]. Conference paper at AAMAS 2019. 2019 ;[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/700e5786-bb0b-4a56-9a0a-f31ed12bab47/Distributional-Reinforcement-Learning-Applied-to-Robot-Soccer-Simulation.pdf
    • Vancouver

      Silva FL da, Reali Costa AH, Stone P. Distributional reinforcement learning applied to robot soccer simulation [Internet]. Conference paper at AAMAS 2019. 2019 ;[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/700e5786-bb0b-4a56-9a0a-f31ed12bab47/Distributional-Reinforcement-Learning-Applied-to-Robot-Soccer-Simulation.pdf
  • Source: Image and Vision Computing. Unidade: EP

    Subjects: VISÃO COMPUTACIONAL, IMAGEM 3D

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      PERAFAN VILLOTA, Juan Carlos et al. Pairwise registration in indoor environments using adaptive combination of 2D and 3D cues. Image and Vision Computing, v. 69, p. 113-124, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.imavis.2017.08.008. Acesso em: 24 abr. 2026.
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      Perafan Villota, J. C., Reali Costa, A. H., Silva, F. L. da, & Jacomini, R. de S. (2018). Pairwise registration in indoor environments using adaptive combination of 2D and 3D cues. Image and Vision Computing, 69, 113-124. doi:10.1016/j.imavis.2017.08.008
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      Perafan Villota JC, Reali Costa AH, Silva FL da, Jacomini R de S. Pairwise registration in indoor environments using adaptive combination of 2D and 3D cues [Internet]. Image and Vision Computing. 2018 ; 69 113-124.[citado 2026 abr. 24 ] Available from: https://doi.org/10.1016/j.imavis.2017.08.008
    • Vancouver

      Perafan Villota JC, Reali Costa AH, Silva FL da, Jacomini R de S. Pairwise registration in indoor environments using adaptive combination of 2D and 3D cues [Internet]. Image and Vision Computing. 2018 ; 69 113-124.[citado 2026 abr. 24 ] Available from: https://doi.org/10.1016/j.imavis.2017.08.008
  • Source: Proceedings. Conference titles: International Joint Conference on Artificial Intelligence - IJCAI. Unidade: EP

    Subjects: SISTEMAS MULTIAGENTES, AGENTES INTELIGENTES, APRENDIZADO COMPUTACIONAL, CONHECIMENTO

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      SILVA, Felipe Leno da e TAYLOR, Matthew E. e REALI COSTA, Anna Helena. Autonomously reusing knowledge in multiagent reinforcement learning. 2018, Anais.. [S. l.]: Escola Politécnica, Universidade de São Paulo, 2018. Disponível em: https://doi.org/10.24963/ijcai.2018/774. Acesso em: 24 abr. 2026.
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      Silva, F. L. da, Taylor, M. E., & Reali Costa, A. H. (2018). Autonomously reusing knowledge in multiagent reinforcement learning. In Proceedings. [S. l.]: Escola Politécnica, Universidade de São Paulo. doi:10.24963/ijcai.2018/774
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      Silva FL da, Taylor ME, Reali Costa AH. Autonomously reusing knowledge in multiagent reinforcement learning [Internet]. Proceedings. 2018 ;[citado 2026 abr. 24 ] Available from: https://doi.org/10.24963/ijcai.2018/774
    • Vancouver

      Silva FL da, Taylor ME, Reali Costa AH. Autonomously reusing knowledge in multiagent reinforcement learning [Internet]. Proceedings. 2018 ;[citado 2026 abr. 24 ] Available from: https://doi.org/10.24963/ijcai.2018/774
  • Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: EP

    Subjects: APRENDIZADO COMPUTACIONAL, AGENTES INTELIGENTES, PROGRAMAÇÃO ORIENTADA A OBJETOS

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      BONINI, Rodrigo Cesar et al. A framework to discover and reuse object-oriented options in reinforcement learning. 2018, Anais.. Piscataway: Escola Politécnica, Universidade de São Paulo, 2018. Disponível em: https://doi.org/10.1109/BRACIS.2018.00027. Acesso em: 24 abr. 2026.
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      Bonini, R. C., Silva, F. L. da, Glatt, R., Spina, E., & Reali Costa, A. H. (2018). A framework to discover and reuse object-oriented options in reinforcement learning. In Proceedings. Piscataway: Escola Politécnica, Universidade de São Paulo. doi:10.1109/BRACIS.2018.00027
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      Bonini RC, Silva FL da, Glatt R, Spina E, Reali Costa AH. A framework to discover and reuse object-oriented options in reinforcement learning [Internet]. Proceedings. 2018 ;[citado 2026 abr. 24 ] Available from: https://doi.org/10.1109/BRACIS.2018.00027
    • Vancouver

      Bonini RC, Silva FL da, Glatt R, Spina E, Reali Costa AH. A framework to discover and reuse object-oriented options in reinforcement learning [Internet]. Proceedings. 2018 ;[citado 2026 abr. 24 ] Available from: https://doi.org/10.1109/BRACIS.2018.00027
  • Source: AAMAS 2018:conference paper. Conference titles: International Conference on Autonomous Agents and Multiagent Systems. Unidade: EP

    Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZAGEM PROFUNDA, TRANSFERÊNCIA (APRENDIZAGEM), SISTEMAS MULTIAGENTES

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      SILVA, Felipe Leno da e REALI COSTA, Anna Helena. Object-oriented curriculum generation for reinforcement learning. 2018, Anais.. [S.l.]: International Foundation for Autonomous Agents and Multiagent Systems, 2018. Disponível em: https://repositorio.usp.br/directbitstream/12eb17e2-5fc4-404b-b758-44c8df4c3f31/Object_oriented_curriculum_generation_for_reinforcement_learning.pdf. Acesso em: 24 abr. 2026.
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      Silva, F. L. da, & Reali Costa, A. H. (2018). Object-oriented curriculum generation for reinforcement learning. In AAMAS 2018:conference paper. [S.l.]: International Foundation for Autonomous Agents and Multiagent Systems. Recuperado de https://repositorio.usp.br/directbitstream/12eb17e2-5fc4-404b-b758-44c8df4c3f31/Object_oriented_curriculum_generation_for_reinforcement_learning.pdf
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      Silva FL da, Reali Costa AH. Object-oriented curriculum generation for reinforcement learning [Internet]. AAMAS 2018:conference paper. 2018 ;[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/12eb17e2-5fc4-404b-b758-44c8df4c3f31/Object_oriented_curriculum_generation_for_reinforcement_learning.pdf
    • Vancouver

      Silva FL da, Reali Costa AH. Object-oriented curriculum generation for reinforcement learning [Internet]. AAMAS 2018:conference paper. 2018 ;[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/12eb17e2-5fc4-404b-b758-44c8df4c3f31/Object_oriented_curriculum_generation_for_reinforcement_learning.pdf
  • Source: Journal of Computational Biology. Unidade: EP

    Assunto: FRAMEWORKS

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      JACOMINI, Ricardo de Souza et al. GeNICE: a Novel Framework for Gene Network Inference by Clustering, Exhaustive Search, and Multivariate Analysis. Journal of Computational Biology, 2017Tradução . . Disponível em: https://doi.org/10.1089/cmb.2017.0022. Acesso em: 24 abr. 2026.
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      Jacomini, R. de S., Martins-Jr, D., Silva, F. L. da, & Reali Costa, A. H. (2017). GeNICE: a Novel Framework for Gene Network Inference by Clustering, Exhaustive Search, and Multivariate Analysis. Journal of Computational Biology. doi:10.1089/cmb.2017.0022
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      Jacomini R de S, Martins-Jr D, Silva FL da, Reali Costa AH. GeNICE: a Novel Framework for Gene Network Inference by Clustering, Exhaustive Search, and Multivariate Analysis [Internet]. Journal of Computational Biology. 2017 ;[citado 2026 abr. 24 ] Available from: https://doi.org/10.1089/cmb.2017.0022
    • Vancouver

      Jacomini R de S, Martins-Jr D, Silva FL da, Reali Costa AH. GeNICE: a Novel Framework for Gene Network Inference by Clustering, Exhaustive Search, and Multivariate Analysis [Internet]. Journal of Computational Biology. 2017 ;[citado 2026 abr. 24 ] Available from: https://doi.org/10.1089/cmb.2017.0022
  • Source: AAAI 2017. Conference titles: Conference on Artificial Intelligence,. Unidade: EP

    Subjects: SISTEMAS MULTIAGENTES, TOMADA DE DECISÃO, INTELIGÊNCIA ARTIFICIAL, APRENDIZAGEM

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      SILVA, Felipe Leno da e GLATT, Ruben e REALI COSTA, Anna Helena. An advising framework for multiagent reinforcement learning systems. 2017, Anais.. [S.l.]: AAAI press, 2017. Disponível em: https://repositorio.usp.br/directbitstream/45891df8-9b38-40bc-9d81-06ae225a8473/An_Advising_Framework_for_Multiagent_Reinforcement_Learning_Systems.pdf. Acesso em: 24 abr. 2026.
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      Silva, F. L. da, Glatt, R., & Reali Costa, A. H. (2017). An advising framework for multiagent reinforcement learning systems. In AAAI 2017. [S.l.]: AAAI press. Recuperado de https://repositorio.usp.br/directbitstream/45891df8-9b38-40bc-9d81-06ae225a8473/An_Advising_Framework_for_Multiagent_Reinforcement_Learning_Systems.pdf
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      Silva FL da, Glatt R, Reali Costa AH. An advising framework for multiagent reinforcement learning systems [Internet]. AAAI 2017. 2017 ;[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/45891df8-9b38-40bc-9d81-06ae225a8473/An_Advising_Framework_for_Multiagent_Reinforcement_Learning_Systems.pdf
    • Vancouver

      Silva FL da, Glatt R, Reali Costa AH. An advising framework for multiagent reinforcement learning systems [Internet]. AAAI 2017. 2017 ;[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/45891df8-9b38-40bc-9d81-06ae225a8473/An_Advising_Framework_for_Multiagent_Reinforcement_Learning_Systems.pdf
  • Source: AAAI 2017. Conference titles: Conference on Artificial Intelligence,. Unidade: EP

    Subjects: SISTEMAS MULTIAGENTES, TOMADA DE DECISÃO

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      SILVA, Felipe Leno da e REALI COSTA, Anna Helena. Accelerating multiagent reinforcement learning through transfer learning. 2017, Anais.. [S.l.]: AAAI press, 2017. Disponível em: https://repositorio.usp.br/directbitstream/1bec9e39-54ce-4fa2-85a9-3ab3ca4b4fca/Accelerating_multiagent_reinforcement_learning_through_transfer_learling.pdf. Acesso em: 24 abr. 2026.
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      Silva, F. L. da, & Reali Costa, A. H. (2017). Accelerating multiagent reinforcement learning through transfer learning. In AAAI 2017. [S.l.]: AAAI press. Recuperado de https://repositorio.usp.br/directbitstream/1bec9e39-54ce-4fa2-85a9-3ab3ca4b4fca/Accelerating_multiagent_reinforcement_learning_through_transfer_learling.pdf
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      Silva FL da, Reali Costa AH. Accelerating multiagent reinforcement learning through transfer learning [Internet]. AAAI 2017. 2017 ;[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/1bec9e39-54ce-4fa2-85a9-3ab3ca4b4fca/Accelerating_multiagent_reinforcement_learning_through_transfer_learling.pdf
    • Vancouver

      Silva FL da, Reali Costa AH. Accelerating multiagent reinforcement learning through transfer learning [Internet]. AAAI 2017. 2017 ;[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/1bec9e39-54ce-4fa2-85a9-3ab3ca4b4fca/Accelerating_multiagent_reinforcement_learning_through_transfer_learling.pdf
  • Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: EP

    Subjects: AGENTES INTELIGENTES, APRENDIZAGEM PROFUNDA, CONHECIMENTO

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      GLATT, Ruben e SILVA, Felipe Leno da e REALI COSTA, Anna Helena. Towards knowledge transfer in deep reinforcement learning. 2017, Anais.. Piscataway: Escola Politécnica, Universidade de São Paulo, 2017. Disponível em: https://doi.org/10.1109/BRACIS.2016.027. Acesso em: 24 abr. 2026.
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      Glatt, R., Silva, F. L. da, & Reali Costa, A. H. (2017). Towards knowledge transfer in deep reinforcement learning. In Proceedings. Piscataway: Escola Politécnica, Universidade de São Paulo. doi:10.1109/BRACIS.2016.027
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      Glatt R, Silva FL da, Reali Costa AH. Towards knowledge transfer in deep reinforcement learning [Internet]. Proceedings. 2017 ;[citado 2026 abr. 24 ] Available from: https://doi.org/10.1109/BRACIS.2016.027
    • Vancouver

      Glatt R, Silva FL da, Reali Costa AH. Towards knowledge transfer in deep reinforcement learning [Internet]. Proceedings. 2017 ;[citado 2026 abr. 24 ] Available from: https://doi.org/10.1109/BRACIS.2016.027
  • Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: EP

    Subjects: APRENDIZADO COMPUTACIONAL, PROCESSOS DE MARKOV, PROGRAMAÇÃO ORIENTADA A OBJETOS, SISTEMAS MULTIAGENTES, ALGORITMOS

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      SILVA, Felipe Leno da e GLATT, Ruben e REALI COSTA, Anna Helena. Object-oriented reinforcement learning in cooperative multiagent domains. 2017, Anais.. Piscataway: Escola Politécnica, Universidade de São Paulo, 2017. Disponível em: https://doi.org/10.1109/BRACIS.2016.015. Acesso em: 24 abr. 2026.
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      Silva, F. L. da, Glatt, R., & Reali Costa, A. H. (2017). Object-oriented reinforcement learning in cooperative multiagent domains. In Proceedings. Piscataway: Escola Politécnica, Universidade de São Paulo. doi:10.1109/BRACIS.2016.015
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      Silva FL da, Glatt R, Reali Costa AH. Object-oriented reinforcement learning in cooperative multiagent domains [Internet]. Proceedings. 2017 ;[citado 2026 abr. 24 ] Available from: https://doi.org/10.1109/BRACIS.2016.015
    • Vancouver

      Silva FL da, Glatt R, Reali Costa AH. Object-oriented reinforcement learning in cooperative multiagent domains [Internet]. Proceedings. 2017 ;[citado 2026 abr. 24 ] Available from: https://doi.org/10.1109/BRACIS.2016.015
  • Source: AAMAS 2017: Proceedings. Conference titles: Workshop on Transfer in Reinforcement Learning. Unidade: EP

    Subjects: TRANSFERÊNCIA (APRENDIZAGEM), APRENDIZAGEM PROFUNDA, SISTEMAS MULTIAGENTES

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      SILVA, Felipe Leno da e REALI COSTA, Anna Helena. Towards zero-shot autonomous inter-task mapping through object-oriented task description. 2017, Anais.. [S.l.]: International Foundation for Autonomous Agents and Multiagent Systems, 2017. Disponível em: https://repositorio.usp.br/directbitstream/2ed493e8-1e0f-4d2b-9fd5-b51294e2d826/Towards-Zero-Shot-Autonomous-Inter-Task-Mapping-through-Object-Oriented-Task-Description.pdf. Acesso em: 24 abr. 2026.
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      Silva, F. L. da, & Reali Costa, A. H. (2017). Towards zero-shot autonomous inter-task mapping through object-oriented task description. In AAMAS 2017: Proceedings. [S.l.]: International Foundation for Autonomous Agents and Multiagent Systems. Recuperado de https://repositorio.usp.br/directbitstream/2ed493e8-1e0f-4d2b-9fd5-b51294e2d826/Towards-Zero-Shot-Autonomous-Inter-Task-Mapping-through-Object-Oriented-Task-Description.pdf
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      Silva FL da, Reali Costa AH. Towards zero-shot autonomous inter-task mapping through object-oriented task description [Internet]. AAMAS 2017: Proceedings. 2017 ;[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/2ed493e8-1e0f-4d2b-9fd5-b51294e2d826/Towards-Zero-Shot-Autonomous-Inter-Task-Mapping-through-Object-Oriented-Task-Description.pdf
    • Vancouver

      Silva FL da, Reali Costa AH. Towards zero-shot autonomous inter-task mapping through object-oriented task description [Internet]. AAMAS 2017: Proceedings. 2017 ;[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/2ed493e8-1e0f-4d2b-9fd5-b51294e2d826/Towards-Zero-Shot-Autonomous-Inter-Task-Mapping-through-Object-Oriented-Task-Description.pdf
  • Source: AAMAS 2017: Proceedings. Conference titles: International Conference on Autonomous Agents and Multiagent Systems. Unidade: EP

    Subjects: TRANSFERÊNCIA (APRENDIZAGEM), SISTEMAS MULTIAGENTES, ACONSELHAMENTO

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      SILVA, Felipe Leno da e GLATT, Ruben e REALI COSTA, Anna Helena. Simultaneously learning and advising in multiagent reinforcement learning. 2017, Anais.. [S.l.]: International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2017. Disponível em: https://repositorio.usp.br/directbitstream/3ee7795f-1d6f-41d4-ac8e-41326445ed0c/Simultaneously_Learning_and_Advising_in_Multiagent.pdf. Acesso em: 24 abr. 2026.
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      Silva, F. L. da, Glatt, R., & Reali Costa, A. H. (2017). Simultaneously learning and advising in multiagent reinforcement learning. In AAMAS 2017: Proceedings. [S.l.]: International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). Recuperado de https://repositorio.usp.br/directbitstream/3ee7795f-1d6f-41d4-ac8e-41326445ed0c/Simultaneously_Learning_and_Advising_in_Multiagent.pdf
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      Silva FL da, Glatt R, Reali Costa AH. Simultaneously learning and advising in multiagent reinforcement learning [Internet]. AAMAS 2017: Proceedings. 2017 ;[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/3ee7795f-1d6f-41d4-ac8e-41326445ed0c/Simultaneously_Learning_and_Advising_in_Multiagent.pdf
    • Vancouver

      Silva FL da, Glatt R, Reali Costa AH. Simultaneously learning and advising in multiagent reinforcement learning [Internet]. AAMAS 2017: Proceedings. 2017 ;[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/3ee7795f-1d6f-41d4-ac8e-41326445ed0c/Simultaneously_Learning_and_Advising_in_Multiagent.pdf
  • Source: AAAI Workshop 2017 - Technical Report. Conference titles: AAAI Conference on Artificial Intelligence - Workshop on Human-Machine Collaborative Learning. Unidade: EP

    Subjects: APRENDIZAGEM PROFUNDA, JOGOS DE COMPUTADOR, SEGURANÇA DE REDES

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      BONINI, Rodrigo Cesar et al. Using options to accelerate learning of new tasks according to human preferences. 2017, Anais.. [Washington]: Association for the Advancement of Artificial Intelligence, 2017. Disponível em: https://repositorio.usp.br/directbitstream/69cb2014-e404-4963-99c4-7564ab000a5d/Using_Options_to_Accelerate_Learning_of_new_tasks_according_to_humam_preferences.pdf. Acesso em: 24 abr. 2026.
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      Bonini, R. C., Silva, F. L. da, Spina, E., & Reali Costa, A. H. (2017). Using options to accelerate learning of new tasks according to human preferences. In AAAI Workshop 2017 - Technical Report. [Washington]: Association for the Advancement of Artificial Intelligence. Recuperado de https://repositorio.usp.br/directbitstream/69cb2014-e404-4963-99c4-7564ab000a5d/Using_Options_to_Accelerate_Learning_of_new_tasks_according_to_humam_preferences.pdf
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      Bonini RC, Silva FL da, Spina E, Reali Costa AH. Using options to accelerate learning of new tasks according to human preferences [Internet]. AAAI Workshop 2017 - Technical Report. 2017 ;[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/69cb2014-e404-4963-99c4-7564ab000a5d/Using_Options_to_Accelerate_Learning_of_new_tasks_according_to_humam_preferences.pdf
    • Vancouver

      Bonini RC, Silva FL da, Spina E, Reali Costa AH. Using options to accelerate learning of new tasks according to human preferences [Internet]. AAAI Workshop 2017 - Technical Report. 2017 ;[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/69cb2014-e404-4963-99c4-7564ab000a5d/Using_Options_to_Accelerate_Learning_of_new_tasks_according_to_humam_preferences.pdf
  • Source: CEUR Workshop Proceedings. Conference titles: Workshop on Advances in Bioinformatics and Artificial Intelligence - BAI 2016. Unidade: EP

    Subjects: INTELIGÊNCIA ARTIFICIAL, BIOINFORMÁTICA, ANÁLISE MULTIVARIADA

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      JACOMINI, Ricardo de Souza et al. A framework for scalable inference of temporal gene regulatory networks based on clustering and multivariate analysis. CEUR Workshop Proceedings, v. 1718, p. 7-13, 2016Tradução . . Disponível em: https://repositorio.usp.br/directbitstream/0d54456f-5e66-4b0a-8c3d-27cc1b3c1ea4/A_framework_for_scalable_inference_of_temporal_gene_regulatory_networks_based_on_clustering_and_multivariate_analysis.pdf. Acesso em: 24 abr. 2026.
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      Jacomini, R. de S., Martins Júnior, D. C., Silva, F. L. da, & Reali Costa, A. H. (2016). A framework for scalable inference of temporal gene regulatory networks based on clustering and multivariate analysis. CEUR Workshop Proceedings, 1718, 7-13. Recuperado de https://repositorio.usp.br/directbitstream/0d54456f-5e66-4b0a-8c3d-27cc1b3c1ea4/A_framework_for_scalable_inference_of_temporal_gene_regulatory_networks_based_on_clustering_and_multivariate_analysis.pdf
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      Jacomini R de S, Martins Júnior DC, Silva FL da, Reali Costa AH. A framework for scalable inference of temporal gene regulatory networks based on clustering and multivariate analysis [Internet]. CEUR Workshop Proceedings. 2016 ; 1718 7-13.[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/0d54456f-5e66-4b0a-8c3d-27cc1b3c1ea4/A_framework_for_scalable_inference_of_temporal_gene_regulatory_networks_based_on_clustering_and_multivariate_analysis.pdf
    • Vancouver

      Jacomini R de S, Martins Júnior DC, Silva FL da, Reali Costa AH. A framework for scalable inference of temporal gene regulatory networks based on clustering and multivariate analysis [Internet]. CEUR Workshop Proceedings. 2016 ; 1718 7-13.[citado 2026 abr. 24 ] Available from: https://repositorio.usp.br/directbitstream/0d54456f-5e66-4b0a-8c3d-27cc1b3c1ea4/A_framework_for_scalable_inference_of_temporal_gene_regulatory_networks_based_on_clustering_and_multivariate_analysis.pdf
  • Source: Anais. Conference titles: Encontro Nacional de Inteligência Artificial e Computacional - ENIAC. Unidades: IME, EP

    Subjects: PROCESSOS DE MARKOV, PROCESSOS ESTOCÁSTICOS, INTELIGÊNCIA ARTIFICIAL

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      SIMÃO, Thiago Dias e BARROS, Leliane Nunes de e SILVA, Felipe Leno da. Planejamento probabilístico com becos sem saída. 2015, Anais.. Porto Alegre: SBC, 2015. Disponível em: http://www.lbd.dcc.ufmg.br/colecoes/eniac/2015/025.pdf. Acesso em: 24 abr. 2026.
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      Simão, T. D., Barros, L. N. de, & Silva, F. L. da. (2015). Planejamento probabilístico com becos sem saída. In Anais. Porto Alegre: SBC. Recuperado de http://www.lbd.dcc.ufmg.br/colecoes/eniac/2015/025.pdf
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      Simão TD, Barros LN de, Silva FL da. Planejamento probabilístico com becos sem saída [Internet]. Anais. 2015 ;[citado 2026 abr. 24 ] Available from: http://www.lbd.dcc.ufmg.br/colecoes/eniac/2015/025.pdf
    • Vancouver

      Simão TD, Barros LN de, Silva FL da. Planejamento probabilístico com becos sem saída [Internet]. Anais. 2015 ;[citado 2026 abr. 24 ] Available from: http://www.lbd.dcc.ufmg.br/colecoes/eniac/2015/025.pdf

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