منابع مشابه
HQ-Learning
HQ-learning is a hierarchical extension of Q()-learning designed to solve certain types of partially observable Markov decision problems (POMDPs). HQ automatically decomposes POMDPs into sequences of simpler subtasks that can be solved by memoryless policies learn-able by reactive subagents. HQ can solve partially observable mazes with more states than those used in most previous POMDP work.
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This short literature review argues that the Resource-Based View (RBV) school of strategic management has recently become of increased interest to scholars of healthcare organizations. RBV links well to the broader interest in more effective Knowledge Mobilization (KM) in healthcare. The paper outlines and discusses key concepts, texts and authors from the RBV tradition and gives recent example...
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ژورنال
عنوان ژورنال: College & Research Libraries News
سال: 1981
ISSN: 2150-6698,0099-0086
DOI: 10.5860/crln.42.9.319