The impact of political parties on public support for European integration
United Kingdom
Water Allocation Improvement in River Basin Using Adaptive Neural Fuzzy Reinforcement Learning Approach
The research leading to this paper was conducted at the Shiraz University, Iran. The measured data were collected by Fars Regional Water Authority ? Iran, and Fars Agricultural Research Center ? Iran. The authors are grateful to Dr. B. Zahraie from University of Tehran, Sh. Araghi ? Nejhad and Reza Karachian Ph. D. Candidates of Amir Kabir Universi...
Reinforcement Learning Embedded in Brains and Robots
This work has been funded partially by the EU project MirrorBot, grant IST-2001-35282, and NEST-043374 coordinated by SW. CW, JT and AF are supported by the Hertie Foundation, and the EU projects PLICON, grant MEXT-CT-2006-042484, and Daisy, grant FP6-2005015803. Urs Bergmann provided feedback on the manuscript.
Model-Free Learning Control of Chemical Processes
Reinforcement Learning-Based Supervisory Control Strategy for a Rotary Kiln Process
In this chapter, we focus on the discussion about an implementation strategy of how to employ reinforcement learning in control of a typical complex industrial process to enhance control performance and adaptability for the variations of operating conditions of the automatic control system. Operation of large rotary kilns is difficult and relies on...
Application on Reinforcement Learning for Diagnosis Based on Medical Image
This work presents an overview of current work applying reinforcement learning in medical image applications, presenting a detailed illustration of a particular use for lung nodules classification. The addressed application of reinforcement learning to solve the problem of lung nodules classification used the 3D geometric nodules characteristics to...
Superposition-Inspired Reinforcement Learning and Quantum Reinforcement Learning
According to the existing problems in RL area, such as low learning speed and tradeoff between exploration and exploitation, SIRL and QRL methods are introduced based on the theory of RL and quantum computation in this chapter, which follows the developing roadmap from the superposition-inspired methods to the RL methods in quantum systems. Just as...
Dynamics of the Bush-Mosteller Learning Algorithm in 2x2 Games
This chapter has characterised the behaviour of the Bush-Mosteller (Bush & Mosteller, 1955) aspiration-based reinforcement learning model in 2x2 games. The dynamics of this process depend mainly on three features: The speed of learning. The existence of self-reinforcing equilibria (SREs). SREs are states which are particularly relevant for the ultr...
Reinforcement Learning for Building Environmental Control
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Abstraction for Genetics-Based Reinforcement Learning
Abstraction may appear a trivial task for humans and the positive results from this work intuitive, but abstraction has not been routinely used in genetics-based reinforcement learning. One reason is that the time each iteration requires is an important consideration and abstraction increases the time for each iteration. Typically XCS takes 20 minu...
