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Minimum Description Length Control
[article]
2022
arXiv
pre-print
We propose a novel framework for multitask reinforcement learning based on the minimum description length (MDL) principle. In this approach, which we term MDL-control (MDL-C), the agent learns the common structure among the tasks with which it is faced and then distills it into a simpler representation which facilitates faster convergence and generalization to new tasks. In doing so, MDL-C naturally balances adaptation to each task with epistemic uncertainty about the task distribution. We
arXiv:2207.08258v3
fatcat:feuhufw4vfhhxc5nufhvuy2bla