Moving Developmental Research Online: Comparing In-Lab and Web-Based Studies of Model-Based Reinforcement Learning
نویسندگان
چکیده
منابع مشابه
Online Constrained Model-based Reinforcement Learning
Applying reinforcement learning to robotic systems poses a number of challenging problems. A key requirement is the ability to handle continuous state and action spaces while remaining within a limited time and resource budget. Additionally, for safe operation, the system must make robust decisions under hard constraints. To address these challenges, we propose a model based approach that combi...
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Reinforcement learning (RL) refers to a wide range of dierent learning algorithms for improving a behavioral policy on the basis of numerical reward signals that serve as feedback. In its basic form, reinforcement learning bears striking resemblance to ‘operant conditioning’ in psychology and animal learning: actions that are rewarded tend to occur more frequently; actions that are punished ar...
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Reinforcement Learning (RL) refers to learning to behave optimally in a stochastic environment by taking actions and receiving rewards [1]. The environment is assumed Markovian in that there is a fixed probability of the next state given the current state and the agent’s action. The agent also receives an immediate reward based on the current state and the action. Models of the next-state distr...
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ژورنال
عنوان ژورنال: Collabra: Psychology
سال: 2020
ISSN: 2474-7394
DOI: 10.1525/collabra.17213