首页|Researchers from Maynooth University Report Findings in Engineering (A Kernel-ba sed Approximate Dynamic Programming Approach: Theory and Application)
Researchers from Maynooth University Report Findings in Engineering (A Kernel-ba sed Approximate Dynamic Programming Approach: Theory and Application)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on En gineering. According to news originating from Kildare, Ireland, by NewsRx corres pondents, research stated, "This article proposes a novel kernel -based Dynamic Programming (DP) approximation method to tackle the typical curse of dimensional ity of stochastic DP problems over the finite time horizon. Such a method utiliz es kernel functions in combination with Support Vector Machine (SVM) regression to determine an approximate cost function for the entire state space of the unde rlying Markov Decision Process (MDP), by leveraging cost function computed for s elected representative states." Our news journalists obtained a quote from the research from Maynooth University , "Kernel functions are used to define the so-called kernel matrix, while the pa rameter vector of the given kernel -based cost function approximation is compute d by moving backwards in time from the terminal condition and by applying SVM re gression. This way, the difficulty of selecting a proper set of features is also tackled. The proposed method is then extended to the infinite time horizon case ."
KildareIrelandEuropeEngineeringD ynamic ProgrammingEmerging TechnologiesMachine LearningMaynooth University
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