Meta-Optimization of Bias-Variance Trade-Off in Stochastic Model Learning
Model-based reinforcement learning is expected to be a method that can safely acquire the optimal policy under real-world conditions by using a stochastic dynamics model for planning. Since the stochastic dynamics model of the real world is generally unknown, a method for learning from state transit...
Saved in:
Main Authors: | Takumi Aotani, Taisuke Kobayashi, Kenji Sugimoto |
---|---|
Format: | article |
Language: | EN |
Published: |
IEEE
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/af14030d799748c8865f08da2aa6ba56 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Reliability-based multiobjective optimization using the satisficing trade-off method
by: Nozomu KOGISO, et al.
Published: (2014) -
Time-Cost-Quality trade off in Critical Chain Method with multi mode activities by Multi Objective Particle Swarm Optimization
by: Mohammad Javad Taheri Amiri, et al.
Published: (2019) -
Predicting length of stay in hospitals intensive care unit using general admission features
by: Merhan A. Abd-Elrazek, et al.
Published: (2021) -
PARETO OPTIMAL SOLUTION OF MULTIOBJECTIVE SYNTHESIS OF ROBUST CONTROLLERS OF MULTIMASS ELECTROMECHANICAL SYSTEMS BASED ON MULTISWARM STOCHASTIC MULTIAGENT OPTIMIZATION
by: T.B. Nikitina
Published: (2017) -
Using Shapley Values and Genetic Algorithms to Solve Multiobjective Optimization Problems
by: Hsien-Chung Wu
Published: (2021)