model-based Q-learning
A Q-learning System for Container Marshalling with Group-Based Learning Model at Container Yard Terminals
... autonomous learning method based on a new learning model considering container-groups and corresponding Q-Learning al- ...described based on the Markov Decision Process ...
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A trust-aware task allocation method using deep q-learning for uncertain mobile crowdsourcing
... sourcing model (MCMDP) is formulated to illustrate the dynamic trust-aware task allocation ...deep Q-learning-based trust-aware task allocation (ImprovedDQL-TTA) algorithm that combines ...
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Reinforcement learning based navigation for autonomous mobile robots in unknown environments
... learned model to be probabilistic. The basic idea is to learn a model that does not predict a deterministic next state and a deterministic reward, but a probability distribution over next states and next ...
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Q-Learning for Robot Control
... as learning the basic control tasks, the algorithm learns to compensate for delays in sensing and actuation by predicting the behaviour of its ...dynamic model is implicit in the controller, it is possible ...
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A Q learning based network content caching method
... reinforcement learning. They extend two re- lated, model-free algorithms for continuous control-deter- ministic policy gradient and stochastic value gradient to solve partially observed domains using ...
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Privacy Preserving Q-learning in the Analog Model for Secure Multiparty Computation
... analog model of ...digital model, one of actions at each position is ...analog model is proposed as a model to realize all directions for behavior ...for Q-learning for the ...
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Human-level Moving Object Recognition from Traffic Video
... Reinforcement learning [2] provides a framework to learn directly from the interaction and achieve ...Reinforcement learning framework is abstract, flexible, and can be applied in many different ...[3] ...
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Implementation of Anomaly Based Network Intrusion Detection by Using Q-learning Technique
... the model and implicitly consider that anomalies can be treated as patterns not observed ...data, based on some measure; we use several detection methods in order to see how efficiently these methods may ...
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Learning Rates for Q-learning
... is based on conver- gence of stochastic iterative algorithms, to derive convergence rates for ...in Q-learning. The first is the synchronous model, where all state action pairs are updated ...
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A Q-learning Based Continuous Tuning of Fuzzy Wall Tracking
... Supervised learning algorithms usually require large amounts of training input/output data, which may be hard to obtain specially for autonomous navigations [13, ...reinforcement learning makes it a ...
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Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems
... reinforcement learning algorithms. We describe a framework that is based on learning the confidence interval around the value function or the Q-function and eliminating actions that are not ...
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Multi objective virtual network embedding algorithm based on Q learning and curiosity driven
... In summary, the proposed method firstly performs multi-objective modeling of deterministic factors as binary (0–1) integer programming problem. Then, it formalizes the virtual node mapping problem using the Markov ...
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Deep Reinforcement Learning of the Model Fusion with Double Q learning
... double q-learning algorithm [6]. Double q-learning that can be generalized to arbitrary function approximation, including deep neural ...DQN. Based on the double q- ...
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Q learning based dynamic joint control of interference and transmission opportunities for cognitive radio
... the Q-learning is a model-free reinforcement learning technique, Q-learning could be very fascinating method for spectrum sensing in time-varying environ- ...used ...
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Ontology based Semantic e Learning Model– A Review
... to learning resources, anytime, anywhere, via a repository of learning resources, but is only concerned with supporting such features as personal definition of learning goals, and synchronous and a ...
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The Application of Group Investigation Based on Hands on Activities to Improve Learning Outcomes Based on Higher Order Thinking Skills of Students at SMA Negeri 2 Pematangsiantar
... Investigation learning model is a part of cooperative learning based on observation to overcome the problems in SMA Negeri 2 ...a learning model based on process ...this ...
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LDA Based Similarity Modeling for Question Answering
... We present an exploration of generative mod- eling for the question answering (QA) task to rank candidate passages. We investigate La- tent Dirichlet Allocation (LDA) models to ob- tain ranking scores based on a ...
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SEARCHING FOR CONSTANT INNOVATION IN TEACHER EDUCATION CURRICULA: THE CASE OF ESTONIA
... science learning are modest and teachers’ satisfaction with their work is ...heavy learning overload and chronic fatigue (reported by 2/3 of respondents), unhealthy habits (about 1/4); a dislike of school ...
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Flipped classroom model for learning evidence-based medicine
... classroom model appears to be an ideal strategy to meet the demands to connect evidence to practice while creating engaged, culturally competent, and technologically literate ...novel model of flipped ...
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PROBLEM SOLVING WITH REINFORCEMENT LEARNING Gavin Adrian Rummery pdf
... reinforcement learning system to solve a simple mobile robot navigation task (which is used as a testbed in chapter ...reinforcement learning has concentrated on discrete Markovian environments, whilst many ...
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