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We present four new reinforcement learning algorithms based on actor–critic, function approximation , and natural gradient ideas, and we provide their convergence proofs. Actor–critic reinforcement learning methods are online approximations to policy iteration in which the value-function parameters are estimated using temporal difference learning and the(More)
We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic reinforcement learning methods are online approximations to policy iteration in which the value-function parameters are estimated using temporal difference learning and the policy parameters are updated(More)
Conversational implicatures are usually described as being licensed by the disobeying or flouting of some principle by the speaker in cooperative dialogue. However, such work has failed to distinguish cases of the speaker flouting such a principle from cases where the speaker is either deceptive or holds a mistaken belief. In this paper, we demonstrate how(More)
We prove the convergence of four new reinforcement learning algorithms based on the actor-critic architecture, on function approximation, and on natural gradients. Reinforcement learning is a class of methods for solving Markov decision processes from sample trajectories under lack of model information. Actor-critic reinforcement learning methods are online(More)
The purpose of this study was to assess an instrument for the peer review of inpatient teaching at Mayo. The Mayo Teaching Evaluation Form (MTEF) is an instrument, based on the Stanford seven-category educational framework, which was developed for the peer review of inpatient teaching. The MTEF has 28 Likert-scaled items derived from the Stanford Faculty(More)
Evidence suggests that inexperienced clinical teachers are often controlling and noninteractive. Adult learning theory states that mature students prefer shared and self-directed learning and that skillful teachers favor facilitating discussions over transmitting knowledge. Similarly, education research shows that effective clinical teachers invest in(More)
OBJECTIVE The objective of this study was to determine whether Internal Medicine residents would find the use of an expert system (i.e. Clinical Diagnostic Decision Support System) to be a satisfactory experience when used during a clinical rotation in the hospital setting. Resident willingness to use the instrument was considered to be of particular(More)
The purpose of this study was to compare the reliability of inpatient teaching evaluations by resident and peer physicians on Mayo internal medicine hospital services. Three resident and three peer evaluators observed 10 consecutively chosen attending physicians on the Mayo hospital services. Evaluations by resident and peer physicians were compared in(More)
BACKGROUND In an era of short inpatient stays, residents may overlook relevant elements of the differential diagnosis as they try to evaluate and treat patients. However, if a resident's first principal diagnosis is wrong, the patient's appropriate evaluation and treatment may take longer, cost more, and lead to worse outcomes. A diagnostic decision support(More)
The National Drug File Reference Terminology contains a novel reference hierarchy to describe physiologic effects (PE) of drugs. The PE reference hierarchy contains 1697 concepts arranged into two broad categories; organ specific and generalized systemic effects. This investigation evaluated the appropriateness of the PE concepts for classifying a random(More)