Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  propose a theoretical and computational framework for approximating the optimal policy in multi-armed bandit problems where the reward distributions are non-Gaussian.  first construct a probabilistic interpolation of the sequence of discrete-time rewards in the form of a continuous-time conditional Levy process. In the Gaussian setting, this approach allows an easy connection to Brownian motion and its convenient time-change properties. No such device is available for non-Gaussian rewards; hover,  show how optimal stopping theory can be used to characterize the value of the optimal policy, using a free-boundary partial integro-differential equation, for exponential and Poisson rewards.  then solve this problem numerically to approximate the set of belief states possessing a given optimal index value, and provide illustrations showing that the solution behaves as expected.
['Zi Ding', 'Ilya O. Ryzhov']
I am writing a research paper on a idea Optimal learning with non-Gaussian rewards
[{"from": "human", "value": "I am writing a research paper on a idea Optimal learning with non-Gaussian rewards"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  propose a theoretical and computational framework for approximating the optimal policy in multi-armed bandit problems where the reward distributions are non-Gaussian.  first construct a probabilistic interpolation of the sequence of discrete-time rewards in the form of a continuous-time conditional Levy process. In the Gaussian setting, this approach allows an easy connection to Brownian motion and its convenient time-change properties. No such device is available for non-Gaussian rewards; hover,  show how optimal stopping theory can be used to characterize the value of the optimal policy, using a free-boundary partial integro-differential equation, for exponential and Poisson rewards.  then solve this problem numerically to approximate the set of belief states possessing a given optimal index value, and provide illustrations showing that the solution behaves as expected."}]