Abstract

The paper deals with a discrete-time consumption investment problem with an infinite horizon. This problem is formulated as a Markov decision process with an expected total discounted utility as an objective function. This paper aims to presents a procedure to approximate the solution via machine learning, specifically, a Q-learning technique. The numerical results of the problem are provided.

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