All Questions
Tagged with reinforcement-learning optimization
8 questions
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In reinforcement learning, does policy affect the maximization of the value?
Though the reward was assigned by the environment, the once the policy $\pi$ was fixed, the probability of the action on the states $\pi(a|s)$ could be assigned.
However, this meant given different ...
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What makes Deep RL "fundamentally/mathematically" advantageous?
Note: I consider myself to be a beginner in the field of Deep RL.
Deep RL has proven tremendous success in recent years like playing atari and beating go champion. Therefore, considerable interest for ...
- 161
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Minimizing the length a Boolean Algebra Expression in disjunctive normal form
I'm looking to minimize the length of an expression in boolean algebra that has been given in disjunctive normal form and is free from redundancy. To remove redundancy from the original expression I ...
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What solution to apply for finding the optimal parameters?
For a study, I have a system (black-box) that requires an input in the form of an array with 4 values (input_array) and depending on their values it produces an ...
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Help needed for understanding proof of No Regret Multi Armed Bandit Algorithm
I was reading Elad Hazan's book on Online Convex Optimization(http://ocobook.cs.princeton.edu/OCObook.pdf) and am facing difficulty understanding the proof given for the No regret algorithm for MAB (...
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Hessian in reinforcement learning
The Hessian of multi-layered network exhibits known behaviour at critical points as shown in [1].
The tools of random matrix theory allow [2] to deduce the asymptotic distribution of the eigenvalues ...
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Markov Decision Process Optimal Policy
Consider the setting of finite MDPs. I will be using the notation in Chapter 2 of http://rll.berkeley.edu/deeprlcourse/docs/ng-thesis.pdf.
Say we have already computed values for the optimal $Q$-...
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Reference request: Introduction to reinforcement learning with hand calculation examples
For me, the most difficulty when it comes to learning about reinforcement learning is that there is not much to learn in the sense that without running some algorithm, it is very difficult to get a ...
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