A Batch, Off-Policy, Actor-Critic Algorithm for Optimizing the Average Reward
arXiv:1607.05047v122 citations
Originality Synthesis-oriented
AI Analysis
This is an incremental method for mobile health applications.
The paper tackled the problem of learning optimal policies from multi-individual data in mobile health by developing an off-policy actor-critic algorithm, but no concrete results or numbers were provided.
We develop an off-policy actor-critic algorithm for learning an optimal policy from a training set composed of data from multiple individuals. This algorithm is developed with a view towards its use in mobile health.