This Continuous U Tree algorithm trans- fers traditional regression tree techniques to reinforcement learning. We have performed experiments in a variety of do-.
The U Tree algorithm generates a tree based state discretization that efficiently finds the relevant state chunks of large propositional domains. In this paper, ...
People also ask
Which reinforcement learning algorithm is specifically designed for problems with continuous action spaces?
What is the concept of state in reinforcement learning?
What is state space in reinforcement learning?
What is an action in reinforcement learning?
This paper extends the U Tree algorithm to challenging domains with a continuous state space for which there is no initial discretization and transfers ...
This Continuous U Tree algorithm transfers traditional regression tree techniques to reinforcement learning. We have performed experiments in a variety of ...
Feb 1, 2023 · Tree Based Discretization for Continuous State Space Reinforcement Learning ; Authors. William R. B. Uther. Manuela M. Veloso ; Proceedings:.
Jan 5, 2019 · Presented algorithm starts from actions initialized by the policy network in the discretized space. Then it explores and evaluates actions with ...
This Continuous U Tree algorithm transfers traditional regression tree techniques to reinforcement learning. We have performed experiments in a variety of ...
Jun 3, 2024 · To address this challenge, the paper proposes a symbolic model that represents behavioral relations, such as alternating simulation from ...
William T. B. Uther and Manuela M. Veloso. Tree Based Discretization for Continuous State Space Reinforcement Learning. In Proceedings of AAAI-98, Madison, WI, ...
Apr 7, 2016 · Reinforcement Learning: The dilemma of choosing discretization steps and performance metrics for continuous action and continuous state space.