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Trabalho de evento
Exploration versus exploitation in model-based reinforcement learning: an empirical study (2022)
Lovatto, Ângelo Gregório ; Barros, Leliane Nunes de ; Mauá, Denis Deratani
Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: IME
Assunto: CONTROLE ÓTIMO
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ABNT
LOVATTO, Ângelo Gregório e BARROS, Leliane Nunes de e MAUÁ, Denis Deratani. Exploration versus exploitation in model-based reinforcement learning: an empirical study. 2022, Anais.. Cham: Springer, 2022. Disponível em: https://doi.org/10.1007/978-3-031-21689-3_3. Acesso em: 11 nov. 2024.
APA
Lovatto, Â. G., Barros, L. N. de, & Mauá, D. D. (2022). Exploration versus exploitation in model-based reinforcement learning: an empirical study. In Proceedings. Cham: Springer. doi:10.1007/978-3-031-21689-3_3
NLM
Lovatto ÂG, Barros LN de, Mauá DD. Exploration versus exploitation in model-based reinforcement learning: an empirical study [Internet]. Proceedings. 2022 ;[citado 2024 nov. 11 ] Available from: https://doi.org/10.1007/978-3-031-21689-3_3
Vancouver
Lovatto ÂG, Barros LN de, Mauá DD. Exploration versus exploitation in model-based reinforcement learning: an empirical study [Internet]. Proceedings. 2022 ;[citado 2024 nov. 11 ] Available from: https://doi.org/10.1007/978-3-031-21689-3_3
Trabalho de evento
Gradient estimation in model-based reinforcement learning: a study on linear quadratic environments (2021)
Lovatto, Ângelo Gregório ; Bueno, Thiago Pereira ; Barros, Leliane Nunes de
Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: IME
Subjects: MODELOS PARA PROCESSOS ESTOCÁSTICOS, APRENDIZADO COMPUTACIONAL
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ABNT
LOVATTO, Ângelo Gregório e BUENO, Thiago Pereira e BARROS, Leliane Nunes de. Gradient estimation in model-based reinforcement learning: a study on linear quadratic environments. 2021, Anais.. Cham: Springer, 2021. Disponível em: https://doi.org/10.1007/978-3-030-91702-9_3. Acesso em: 11 nov. 2024.
APA
Lovatto, Â. G., Bueno, T. P., & Barros, L. N. de. (2021). Gradient estimation in model-based reinforcement learning: a study on linear quadratic environments. In Proceedings. Cham: Springer. doi:10.1007/978-3-030-91702-9_3
NLM
Lovatto ÂG, Bueno TP, Barros LN de. Gradient estimation in model-based reinforcement learning: a study on linear quadratic environments [Internet]. Proceedings. 2021 ;[citado 2024 nov. 11 ] Available from: https://doi.org/10.1007/978-3-030-91702-9_3
Vancouver
Lovatto ÂG, Bueno TP, Barros LN de. Gradient estimation in model-based reinforcement learning: a study on linear quadratic environments [Internet]. Proceedings. 2021 ;[citado 2024 nov. 11 ] Available from: https://doi.org/10.1007/978-3-030-91702-9_3
Artigo de periodico
Efficient algorithms for Risk-Sensitive Markov Decision Processes with limited budget (2021)
Moreira, Daniel Augusto de Melo; Delgado, Karina Valdivia ; Barros, Leliane Nunes de ; Mauá, Denis Deratani
Source: International Journal of Approximate Reasoning. Unidades: EACH, IME
Subjects: PESQUISA OPERACIONAL, PROGRAMAÇÃO MATEMÁTICA, PROCESSOS DE MARKOV, TEORIA DOS JOGOS, TEORIA DA DECISÃO
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ABNT
MOREIRA, Daniel Augusto de Melo et al. Efficient algorithms for Risk-Sensitive Markov Decision Processes with limited budget. International Journal of Approximate Reasoning, v. 139, p. 143-165, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2021.09.003. Acesso em: 11 nov. 2024.
APA
Moreira, D. A. de M., Delgado, K. V., Barros, L. N. de, & Mauá, D. D. (2021). Efficient algorithms for Risk-Sensitive Markov Decision Processes with limited budget. International Journal of Approximate Reasoning, 139, 143-165. doi:10.1016/j.ijar.2021.09.003
NLM
Moreira DA de M, Delgado KV, Barros LN de, Mauá DD. Efficient algorithms for Risk-Sensitive Markov Decision Processes with limited budget [Internet]. International Journal of Approximate Reasoning. 2021 ; 139 143-165.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.ijar.2021.09.003
Vancouver
Moreira DA de M, Delgado KV, Barros LN de, Mauá DD. Efficient algorithms for Risk-Sensitive Markov Decision Processes with limited budget [Internet]. International Journal of Approximate Reasoning. 2021 ; 139 143-165.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.ijar.2021.09.003
Artigo de periodico
Using mathematical programming to solve factored Markov decision processes with imprecise probabilities (2011)
Delgado, Karina Valdivia; Barros, Leliane Nunes de ; Cozman, Fabio Gagliardi ; Sanner, Scott
Source: International Journal of Approximate Reasoning. Unidades: EACH, IME, EP
Assunto: PROGRAMAÇÃO MATEMÁTICA
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ABNT
DELGADO, Karina Valdivia et al. Using mathematical programming to solve factored Markov decision processes with imprecise probabilities. International Journal of Approximate Reasoning, v. 52, p. 1000-1017, 2011Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2011.04.002. Acesso em: 11 nov. 2024.
APA
Delgado, K. V., Barros, L. N. de, Cozman, F. G., & Sanner, S. (2011). Using mathematical programming to solve factored Markov decision processes with imprecise probabilities. International Journal of Approximate Reasoning, 52, 1000-1017. doi:10.1016/j.ijar.2011.04.002
NLM
Delgado KV, Barros LN de, Cozman FG, Sanner S. Using mathematical programming to solve factored Markov decision processes with imprecise probabilities [Internet]. International Journal of Approximate Reasoning. 2011 ; 52 1000-1017.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.ijar.2011.04.002
Vancouver
Delgado KV, Barros LN de, Cozman FG, Sanner S. Using mathematical programming to solve factored Markov decision processes with imprecise probabilities [Internet]. International Journal of Approximate Reasoning. 2011 ; 52 1000-1017.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.ijar.2011.04.002
Artigo de periodico
Efficient solutions to factored MDPs with imprecise transition probabilities (2011)
Delgado, Karina Valdivia; Sanner, Scott; Barros, Leliane Nunes de
Source: Artificial Intelligence. Unidades: EACH, IME
Assunto: INTELIGÊNCIA ARTIFICIAL
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ABNT
DELGADO, Karina Valdivia e SANNER, Scott e BARROS, Leliane Nunes de. Efficient solutions to factored MDPs with imprecise transition probabilities. Artificial Intelligence, v. 175, n. ju 2011, p. 1498-1527, 2011Tradução . . Disponível em: https://doi.org/10.1016/j.artint.2011.01.001. Acesso em: 11 nov. 2024.
APA
Delgado, K. V., Sanner, S., & Barros, L. N. de. (2011). Efficient solutions to factored MDPs with imprecise transition probabilities. Artificial Intelligence, 175( ju 2011), 1498-1527. doi:10.1016/j.artint.2011.01.001
NLM
Delgado KV, Sanner S, Barros LN de. Efficient solutions to factored MDPs with imprecise transition probabilities [Internet]. Artificial Intelligence. 2011 ; 175( ju 2011): 1498-1527.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.artint.2011.01.001
Vancouver
Delgado KV, Sanner S, Barros LN de. Efficient solutions to factored MDPs with imprecise transition probabilities [Internet]. Artificial Intelligence. 2011 ; 175( ju 2011): 1498-1527.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.artint.2011.01.001
Trabalho de evento
Symbolic dynamic programming for discrete and continuous state MDPs (2011)
Sanner, Scott; Delgado, Karina Valdivia ; Barros, Leliane Nunes de
Source: Proceedings. Conference titles: Conference on Uncertainty in Artificial Intelligence - UAI. Unidades: EACH, IME
Subjects: INTELIGÊNCIA ARTIFICIAL, PROCESSOS DE MARKOV, PROGRAMAÇÃO DINÂMICA
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ABNT
SANNER, Scott e DELGADO, Karina Valdivia e BARROS, Leliane Nunes de. Symbolic dynamic programming for discrete and continuous state MDPs. 2011, Anais.. Arlington: AUAI Press, 2011. Disponível em: https://doi.org/10.5555/3020548.3020623. Acesso em: 11 nov. 2024.
APA
Sanner, S., Delgado, K. V., & Barros, L. N. de. (2011). Symbolic dynamic programming for discrete and continuous state MDPs. In Proceedings. Arlington: AUAI Press. doi:10.5555/3020548.3020623
NLM
Sanner S, Delgado KV, Barros LN de. Symbolic dynamic programming for discrete and continuous state MDPs [Internet]. Proceedings. 2011 ;[citado 2024 nov. 11 ] Available from: https://doi.org/10.5555/3020548.3020623
Vancouver
Sanner S, Delgado KV, Barros LN de. Symbolic dynamic programming for discrete and continuous state MDPs [Internet]. Proceedings. 2011 ;[citado 2024 nov. 11 ] Available from: https://doi.org/10.5555/3020548.3020623
Trabalho de evento
Representing and solving factored Markov decision processes with imprecise probabilities (2009)
Delgado, Karina Valdivia ; Barros, Leliane Nunes de ; Cozman, Fabio Gagliardi ; Shirota, Ricardo
Source: Proceedings. Conference titles: International Symposium on Imprecise Probability: Theories and Applications - ISIPTA. Unidades: IME, EP
Subjects: PROCESSOS DE MARKOV, PROBABILIDADE, REPRESENTAÇÃO DE CONHECIMENTO, PROGRAMAÇÃO LINEAR
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ABNT
DELGADO, Karina Valdivia et al. Representing and solving factored Markov decision processes with imprecise probabilities. 2009, Anais.. Durham: SIPTA, 2009. Disponível em: https://www.sipta.org/isipta09/proceedings/isipta09-proceedings.pdf. Acesso em: 11 nov. 2024.
APA
Delgado, K. V., Barros, L. N. de, Cozman, F. G., & Shirota, R. (2009). Representing and solving factored Markov decision processes with imprecise probabilities. In Proceedings. Durham: SIPTA. Recuperado de https://www.sipta.org/isipta09/proceedings/isipta09-proceedings.pdf
NLM
Delgado KV, Barros LN de, Cozman FG, Shirota R. Representing and solving factored Markov decision processes with imprecise probabilities [Internet]. Proceedings. 2009 ;[citado 2024 nov. 11 ] Available from: https://www.sipta.org/isipta09/proceedings/isipta09-proceedings.pdf
Vancouver
Delgado KV, Barros LN de, Cozman FG, Shirota R. Representing and solving factored Markov decision processes with imprecise probabilities [Internet]. Proceedings. 2009 ;[citado 2024 nov. 11 ] Available from: https://www.sipta.org/isipta09/proceedings/isipta09-proceedings.pdf
Trabalho de evento
Diagnostic of programs for programming learning tools (2006)
Delgado, Karina Valdivia ; Barros, Leliane Nunes de
Source: Proceedings. Conference titles: Ibero-American Conference on Artificial Intelligence - IBERAMIA. Unidade: IME
Subjects: ALGORITMOS, INTELIGÊNCIA ARTIFICIAL, ENGENHARIA DE SOFTWARE, SOLUÇÃO DE PROBLEMAS
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ABNT
DELGADO, Karina Valdivia e BARROS, Leliane Nunes de. Diagnostic of programs for programming learning tools. 2006, Anais.. Berlin: Springer, 2006. Disponível em: https://doi.org/10.1007/11874850_5. Acesso em: 11 nov. 2024.
APA
Delgado, K. V., & Barros, L. N. de. (2006). Diagnostic of programs for programming learning tools. In Proceedings. Berlin: Springer. doi:10.1007/11874850_5
NLM
Delgado KV, Barros LN de. Diagnostic of programs for programming learning tools [Internet]. Proceedings. 2006 ;[citado 2024 nov. 11 ] Available from: https://doi.org/10.1007/11874850_5
Vancouver
Delgado KV, Barros LN de. Diagnostic of programs for programming learning tools [Internet]. Proceedings. 2006 ;[citado 2024 nov. 11 ] Available from: https://doi.org/10.1007/11874850_5
Trabalho de evento
Planning with abduction: a logical framework to explore extensions to classical planning (2004)
Pereira, Silvio do Lago; Barros, Leliane Nunes de
Source: Proceedings. Conference titles: Brazilian Symposium on Artificial Intelligence - SBIA. Unidade: IME
Subjects: INTELIGÊNCIA ARTIFICIAL, PROGRAMAÇÃO LÓGICA
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ABNT
PEREIRA, Silvio do Lago e BARROS, Leliane Nunes de. Planning with abduction: a logical framework to explore extensions to classical planning. 2004, Anais.. Berlin: Springer, 2004. Disponível em: https://doi.org/10.1007/978-3-540-28645-5_7. Acesso em: 11 nov. 2024.
APA
Pereira, S. do L., & Barros, L. N. de. (2004). Planning with abduction: a logical framework to explore extensions to classical planning. In Proceedings. Berlin: Springer. doi:10.1007/978-3-540-28645-5_7
NLM
Pereira S do L, Barros LN de. Planning with abduction: a logical framework to explore extensions to classical planning [Internet]. Proceedings. 2004 ;[citado 2024 nov. 11 ] Available from: https://doi.org/10.1007/978-3-540-28645-5_7
Vancouver
Pereira S do L, Barros LN de. Planning with abduction: a logical framework to explore extensions to classical planning [Internet]. Proceedings. 2004 ;[citado 2024 nov. 11 ] Available from: https://doi.org/10.1007/978-3-540-28645-5_7

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