Results 11 to 20 of about 34,803,504 (287)
Continuous-Time Model-Based Reinforcement Learning [PDF]
CoRR, 2021 Model-based reinforcement learning (MBRL) approaches rely on discrete-time state transition models whereas physical systems and the vast majority of control tasks operate in continuous-time. To avoid time-discretization approximation of the underlying process, we propose a continuous-time MBRL framework based on a novel actor-critic method.
Heinonen Markus +2 more
core +7 more sources
Reinforcement Learning-based Spectrum Sharing for Cognitive Radio [PDF]
, 2011 This thesis investigates how distributed reinforcement learning-based resource assignment algorithms can be used to improve the performance of a cognitive radio system.
Jiang, Tao
core +6 more sources
Improving Exploration in Reinforcement Learning through Domain Knowledge and Parameter Analysis [PDF]
, 2010 This thesis presents novel work on how to improve exploration in reinforcement learning using domain knowledge and knowledge-based approaches to reinforcement learning.
Grzes, Marek
core +7 more sources
Comparing policy gradient and value function based reinforcement learning methods in simulated electrical power trade [PDF]
, 2012 In electrical power engineering, reinforcement learning algorithms can be used to model the strategies of electricity market participants. However, traditional value function based reinforcement learning algorithms suffer from convergence issues when ...
Burt, Graeme +3 more
core +4 more sources
Survey of Reinforcement Learning Based Recommender Systems [PDF]
Jisuanji kexue, 2021 Recommender systems are devoted to find and automatically recommend valuable information and services for users from massive data,which can effectively solve the information overload problem,and become an important information technology in the era of ...
YU Li, DU Qi-han, YUE Bo-yan, XIANG Jun-yao, XU Guan-yu, LENG You-fang
doaj +1 more source
Learning to Paint With Model-Based Deep Reinforcement Learning [PDF]
2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019 Accepted to ICCV ...
Zhewei Huang +2 more
openaire +3 more sources
eLife, 2021 Dopamine is implicated in representing model-free (MF) reward prediction errors a as well as influencing model-based (MB) credit assignment and choice. Putative cooperative interactions between MB and MF systems include a guidance of MF credit assignment
Lorenz Deserno +5 more
doaj +1 more source
Model-based multi-objective reinforcement learning [PDF]
2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL), 2014 This paper describes a novel multi-objective reinforcement learning algorithm. The proposed algorithm first learns a model of the multi-objective sequential decision making problem, after which this learned model is used by a multi-objective dynamic programming method to compute Pareto op-timal policies.
Marco A. Wiering +2 more
openaire +3 more sources
A Unifying Framework for Reinforcement Learning and Planning
Frontiers in Artificial Intelligence, 2022 Sequential decision making, commonly formalized as optimization of a Markov Decision Process, is a key challenge in artificial intelligence. Two successful approaches to MDP optimization are reinforcement learning and planning, which both largely have ...
Thomas M. Moerland +4 more
doaj +1 more source
Entrainable Neural Conversation Model Based on Reinforcement Learning
IEEE Access, 2020 The synchronization of words in conversation, called entrainment, is generally observed in human-human conversations. Entrainment has a high correlation with dialogue success, naturalness, and engagement.
Seiya Kawano +3 more
doaj +1 more source