Learning Control of continuous strengthening of complex systems based on support vector machine View Homepage


Ontology type: schema:MonetaryGrant     


Grant Info

YEARS

2009-2011

FUNDING AMOUNT

180000 CNY

ABSTRACT

In order to solve the learning control problems of complex continuous systems, performance improvement and applications of reinforcement learning algorithms are researched. The reinforcement learning is constructed as a simple binary-class problem, Q leaning algorithms based on a probability support vector machine and a Gaussian process classifier are proposed respectively. Aiming at the curse of dimensionality problem encountered by reinforcement learning methods for elevator group scheduling systems with large-scale state space, a kind of Bayesian reinforcement learning method based on abstraction states is proposed. A kind of Q learning based on a cooperative support vector machine is proposed by using a probability support vector classification machine supplies a support vector regression machine with dynamic and real-time knowledge to accelerate the learning process of value function. A reinforcement learning algorithm based on a semi-parametric support vector regression model by taking advantage of large amount learning experience provided by parametric model. In order to avoid the learning performance of reinforcement learning system worse, which is caused by too much human factors, policy iteration reinforcement learning methods based on basis functions that are constructed automatically on graph are giv More... »

URL

http://npd.nsfc.gov.cn/projectDetail.action?pid=60804022

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