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Hybrid Coordination of Reinforcement Learning-based Behaviors for AUV Control (2001)
| Content Provider | CiteSeerX |
|---|---|
| Author | Carreras, M. Batlle, J. Ridao, P. Pagès, J. |
| Description | This paper proposes a Hybrid Coordination method for Behavior-based Control Architectures. The hybrid method takes in advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper will demonstrate the feasibility of this hybrid method with a 3D-navigation application to an Autonomous Underwater Vehicle (AUV). The behaviors were learnt online by means of Reinforcement Learning. Q(l)- learning was used extending the one-step learning of the popular Q-learning to n-steps. Realistic simulations were carried out. Results showed the good performance of the hybrid method on behavior coordination as well as on increasing and improving behavior learning. |
| File Format | |
| Language | English |
| Publisher Date | 2001-01-01 |
| Publisher Institution | In: IEEE/RSJ IROS |
| Access Restriction | Open |
| Subject Keyword | Hybrid Coordination Behavior Coordination Reinforcement Learning Behavior-based Control Architecture Behavior Learning Reinforcement Learning-based Behavior Hybrid Method One-step Learning Optimized Trajectory Hybrid Coordination Method 3d-navigation Application Autonomous Underwater Vehicle Good Performance Learnt Online Realistic Simulation Cooperative One Auv Control Competitive Approach |
| Content Type | Text |
| Resource Type | Article |
