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تسجيل مستخدم جديدFull Gradient DQN Reinforcement Learning: A Provably Convergent Scheme
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نشر من قبل
Konstantin Avrachenkov
تاريخ النشر
2021
مجال البحث
الهندسة المعلوماتية
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English
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We analyze the DQN reinforcement learning algorithm as a stochastic approximation scheme using the o.d.e. (for ordinary differential equation) approach and point out certain theoretical issues. We then propose a modified scheme called Full Gradient DQN (FG-DQN, for short) that has a sound theoretical basis and compare it with the original scheme on sample problems. We observe a better performance for FG-DQN.
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