Exploration-based model learning with self-attention for risk-sensitive robot control
DongWook Kim,
Sudong Lee,
Tae Hwa Hong
et al.
Abstract:Model-based reinforcement learning for robot control offers the advantages of overcoming concerns on data collection and iterative processes for policy improvement in model-free methods. However, both methods use exploration strategy relying on heuristics that involve inherent randomness, which may cause instability or malfunction of the target system and render the system susceptible to external perturbations. In this paper, we propose an online model update algorithm that can be directly operated in real-wor… Show more
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