Similarity-based transfer learning of decision policies
arXiv:2006.08768v11 citations
Originality Synthesis-oriented
AI Analysis
This addresses policy learning for decision-making systems, but appears incremental as it builds on existing FPD formalism.
The paper tackles the problem of learning decision policies from past experience by proposing a new general approach using the Fully Probabilistic Design formalism to find a stochastic policy.
A problem of learning decision policy from past experience is considered. Using the Fully Probabilistic Design (FPD) formalism, we propose a new general approach for finding a stochastic policy from the past data.