Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
An Introduction to Neural Networks
An Introduction to Neural Networks
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Practical Reinforcement Learning in Continuous Spaces
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Richard Bellman on the Birth of Dynamic Programming
Operations Research
Making reinforcement learning work on real robots
Making reinforcement learning work on real robots
Development of a humanoid robot
International Journal of Computer Applications in Technology
An efficient simplification and real-time rendering algorithm for large-scale terrain
International Journal of Computer Applications in Technology
A 3D shape classifier with neural network supervision
International Journal of Computer Applications in Technology
Hi-index | 0.00 |
This paper presents the mobile robot navigation technique which utilises Reinforcement Learning (RL) algorithms and Artificial Neural Network (ANN) to learn in an unknown environment for mobile robot navigation. This research study is focused on the integration of multi-layer neural network and Q-learning as online learning control scheme. This process is divided into two stages. In the initial stage, the agent will map the environment through collecting state-action information according to the Q-learning procedure. Second training process involves neural network which utilises the state-action information gathered in the earlier phase of training samples. During final application of the controller, Q-learning would be used as primary navigating tool whereas the trained neural network will be employed when approximation is needed. MATLAB simulation was developed to verify and validate the algorithm before real-time implementation using Team AmigoBot™ robot. The results obtained from both simulation and real world experiments are discussed.