On the performance of planning through backpropagation (2020)
- Authors:
- USP affiliated authors: BARROS, LELIANE NUNES DE - IME ; MAUÁ, DENIS DERATANI - IME ; SCARONI, RENATO - IME ; BUENO, THIAGO PEREIRA - IME
- Unidade: IME
- DOI: 10.1007/978-3-030-61380-8_8
- Subjects: APRENDIZAGEM PROFUNDA; COMPUTAÇÃO APLICADA; METODOLOGIA E TÉCNICAS DE COMPUTAÇÃO
- Keywords: gradient based optimization; continuous deterministic planning
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Proceedings
- Conference titles: Brazilian Conference on Intelligent Systems - BRACIS
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
SCARONI, Renato et al. On the performance of planning through backpropagation. 2020, Anais.. Cham: Springer, 2020. Disponível em: https://doi.org/10.1007/978-3-030-61380-8_8. Acesso em: 28 abr. 2024. -
APA
Scaroni, R., Bueno, T. P., Barros, L. N. de, & Mauá, D. D. (2020). On the performance of planning through backpropagation. In Proceedings. Cham: Springer. doi:10.1007/978-3-030-61380-8_8 -
NLM
Scaroni R, Bueno TP, Barros LN de, Mauá DD. On the performance of planning through backpropagation [Internet]. Proceedings. 2020 ;[citado 2024 abr. 28 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_8 -
Vancouver
Scaroni R, Bueno TP, Barros LN de, Mauá DD. On the performance of planning through backpropagation [Internet]. Proceedings. 2020 ;[citado 2024 abr. 28 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_8 - Deep reactive policies for planning in stochastic nonlinear domains
- Decision-aware model learning for actor-critic methods: when theory does not meet practice
- When a robot reaches out for human help
- Gradient estimation in model-based reinforcement learning: a study on linear quadratic environments
- Planning in stochastic computation graphs: solving stochastic nonlinear problems with backpropagation
- Analyzing the effect of stochastic transitions in policy gradients in deep reinforcement learning
- Exploration versus exploitation in model-based reinforcement learning: an empirical study
- A contact network-based approach for online planning of containment measures for COVID-19
- Markov decision processes specified by probabilistic logic programming: representation and solution
- Modeling Markov decision processes with imprecise probabilities using probabilistic logic programming
Informações sobre o DOI: 10.1007/978-3-030-61380-8_8 (Fonte: oaDOI API)
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
