ReP USP - Resultado da busca

Trabalho de evento-resumo
GAN-based data mapping for model adaptation (2021)
Silva, Felipe Leno da ; Glatt, Ruben ; Cobe, Raphael ; Vicente, Renato
Source: Extended abstracts. Conference titles: International Conference on Machine Learning Conference: LatinX in AI - LXAI. Unidade: IME
Assunto: APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVA, Felipe Leno da et al. GAN-based data mapping for model adaptation. 2021, Anais.. San Diego: ICML, 2021. Disponível em: https://doi.org/10.52591/lxai202107242. Acesso em: 04 dez. 2025.
APA
Silva, F. L. da, Glatt, R., Cobe, R., & Vicente, R. (2021). GAN-based data mapping for model adaptation. In Extended abstracts. San Diego: ICML. doi:10.52591/lxai202107242
NLM
Silva FL da, Glatt R, Cobe R, Vicente R. GAN-based data mapping for model adaptation [Internet]. Extended abstracts. 2021 ;[citado 2025 dez. 04 ] Available from: https://doi.org/10.52591/lxai202107242
Vancouver
Silva FL da, Glatt R, Cobe R, Vicente R. GAN-based data mapping for model adaptation [Internet]. Extended abstracts. 2021 ;[citado 2025 dez. 04 ] Available from: https://doi.org/10.52591/lxai202107242
Artigo de periodico
DECAF: deep case-based policy inference for knowledge transfer in reinforcement learning (2020)
Glatt, Ruben; Silva, Felipe Leno da ; Bianchi, Reinaldo Augusto da Costa ; Reali Costa, Anna Helena
Source: Expert Systems with Applications. Unidade: EP
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GLATT, Ruben et al. DECAF: deep case-based policy inference for knowledge transfer in reinforcement learning. Expert Systems with Applications, v. 156, p. 113420, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2020.113420. Acesso em: 04 dez. 2025.
APA
Glatt, R., Silva, F. L. da, Bianchi, R. A. da C., & Reali Costa, A. H. (2020). DECAF: deep case-based policy inference for knowledge transfer in reinforcement learning. Expert Systems with Applications, 156, 113420. doi:10.1016/j.eswa.2020.113420
NLM
Glatt R, Silva FL da, Bianchi RA da C, Reali Costa AH. DECAF: deep case-based policy inference for knowledge transfer in reinforcement learning [Internet]. Expert Systems with Applications. 2020 ; 156 113420.[citado 2025 dez. 04 ] Available from: https://doi.org/10.1016/j.eswa.2020.113420
Vancouver
Glatt R, Silva FL da, Bianchi RA da C, Reali Costa AH. DECAF: deep case-based policy inference for knowledge transfer in reinforcement learning [Internet]. Expert Systems with Applications. 2020 ; 156 113420.[citado 2025 dez. 04 ] Available from: https://doi.org/10.1016/j.eswa.2020.113420
Artigo de periodico
MOO-MDP: an Object-Oriented Representation for Cooperative Multiagent Reinforcement Learning (2019)
Silva, Felipe Leno da ; Reali Costa, Anna Helena ; Glatt, Ruben
Source: IEEE Transactions on Cybernetics. Unidade: EP
Assunto: APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 04 dez. 2025.
APA
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
NLM
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 2025 dez. 04 ] 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 2025 dez. 04 ] Available from: https://doi.org/10.1109/TCYB.2017.2781130
Tese (Doutorado)
Knowledge reuse for deep reinforcement learning (2019)
Glatt, Ruben; Reali Costa, Anna Helena (Orientador)
Unidade: EP
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GLATT, Ruben. Knowledge reuse for deep reinforcement learning. 2019. Tese (Doutorado) – Universidade de São Paulo, São Paulo, 2019. Disponível em: http://www.teses.usp.br/teses/disponiveis/3/3141/tde-18092019-074805/. Acesso em: 04 dez. 2025.
APA
Glatt, R. (2019). Knowledge reuse for deep reinforcement learning (Tese (Doutorado). Universidade de São Paulo, São Paulo. Recuperado de http://www.teses.usp.br/teses/disponiveis/3/3141/tde-18092019-074805/
NLM
Glatt R. Knowledge reuse for deep reinforcement learning [Internet]. 2019 ;[citado 2025 dez. 04 ] Available from: http://www.teses.usp.br/teses/disponiveis/3/3141/tde-18092019-074805/
Vancouver
Glatt R. Knowledge reuse for deep reinforcement learning [Internet]. 2019 ;[citado 2025 dez. 04 ] Available from: http://www.teses.usp.br/teses/disponiveis/3/3141/tde-18092019-074805/
Trabalho de evento
An advising framework for multiagent reinforcement learning systems (2017)
Silva, Felipe Leno da ; Glatt, Ruben ; Reali Costa, Anna Helena
Source: AAAI 2017. Conference titles: Conference on Artificial Intelligence,. Unidade: EP
Subjects: SISTEMAS MULTIAGENTES, TOMADA DE DECISÃO, INTELIGÊNCIA ARTIFICIAL, APRENDIZAGEM
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 04 dez. 2025.
APA
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
NLM
Silva FL da, Glatt R, Reali Costa AH. An advising framework for multiagent reinforcement learning systems [Internet]. AAAI 2017. 2017 ;[citado 2025 dez. 04 ] 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 2025 dez. 04 ] Available from: https://repositorio.usp.br/directbitstream/45891df8-9b38-40bc-9d81-06ae225a8473/An_Advising_Framework_for_Multiagent_Reinforcement_Learning_Systems.pdf

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