Model Based Reinforcement Learning Pre-Trained with Various State Data

Masaaki Ono; Ryutaro Ichise

doi:10.1109/cai59869.2024.00169

ScienceGate Book Chapters

JOURNAL ARTICLE

Model Based Reinforcement Learning Pre-Trained with Various State Data

Masaaki Ono Ryutaro Ichise

Year: 2024 Vol: abs/1606.06565 Pages: 918-925

DOI: 10.1109/cai59869.2024.00169

Get Full-Text PDF Get Analytical Report

Keywords:

Reinforcement learning Computer science Reinforcement State (computer science) Artificial intelligence Machine learning Engineering Structural engineering Programming language

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.10

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Reinforcement Learning in Robotics

Physical Sciences → Computer Science → Artificial Intelligence

Evolutionary Algorithms and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Adaptive Dynamic Programming Control

Physical Sciences → Computer Science → Computational Theory and Mathematics

Model Based Reinforcement Learning Pre-Trained with Various State Data

Metrics

Topics

Related Documents

GPTMORE: Generative Pre-trained Transformer for Model-based Offline Reinforcement Learning

A reinforcement learning intelligent deductive model with pre-trained sequence information

A pre-trained data deduplication model based on active learning

Solar irradiance prediction using reinforcement learning pre-trained with limited historical data

Solar Irradiance Prediction Using Reinforcement Learning Pre-Trained with Few Historical Data