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A Multistrategy Case-Based and Reinforcement Learning Approach to Self-Improving Reactive Control Systems for Autonomous Robotic Navigation
(Georgia Institute of Technology, 1993)
This paper presents a self-improving reactive
control system for autonomous robotic navigation.
The navigation module uses a schema-based
reactive control system to perform the
navigation task. The learning module ...
Knowledge Compilation and Speedup Learning in Continuous Task Domains
(Georgia Institute of Technology, 1993)
Many techniques for speedup learning and
knowledge compilation focus on the learning and
optimization of macro-operators or control rules
in task domains that can be characterized using a
problem-space search paradigm. ...
Multistrategy Learning in Reactive Control Systems for Autonomous Robotic Navigation
(Georgia Institute of Technology, 1993)
This paper presents a self-improving reactive control system for autonomous robotic navigation. The navigation module uses a schema-based reactive control system to perform the navigation task. The learning module combines ...
Experiments With Reinforcement Learning in Problems With Continuous State and Action Spaces
(Georgia Institute of Technology, 1996)
A key element in the solution of reinforcement learning problems is the value function. The purpose of this function is to measure the long-term utility or value of any given state and it is important because an agent can ...
Multistrategy Learning of Adaptive Reactive Controllers
(Georgia Institute of Technology, 1997)
Reactive controllers has been widely used in mobile robots since they are
able to achieve successful performance in real-time. However, the
configuration of a reactive controller depends highly on the operating
conditions ...