Reinforcement Schedules
Reinforcement
Observational Learning
Multi-input and Multi-variable systems
Avoidance Learning and Learned Helplessness
Collisions in Multiple Dimensions: Problem Solving
您也可能阅读
通过共同作者、期刊和引用图与本文相关的文章。
本研究引入了安全强化学习 (RL) 的新框架,该框架平衡了多个目标,同时遵守了安全约束. 该方法有效地优化政策,确保安全并提高复杂的RL任务的性能.
07:05Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
Published on: September 10, 2018
11:53Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
科学领域:
背景情况:
研究的目的:
主要方法:
主要成果:
结论: