Similarity-based transfer learning of decision policies

Autor:	Zugarová, Eliška, Guy, Tatiana V.
Rok vydání:	2020
Předmět:	Computer Science - Machine Learning Computer Science - Artificial Intelligence Electrical Engineering and Systems Science - Systems and Control Statistics - Machine Learning 68T05 (Primary)
Druh dokumentu:	Working Paper
Popis:	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.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2006.08768 Zobrazit plný text záznamu View this record from Arxiv