This paper presents the prototype of the instrument that supports the control of assets and liabilities by a bank using the mathematical computations. The specifics of the approach lies in the application of the recent advances in the control theory to provide the strategic analysis for various planning horizons and scenarios of external and internal factors.

Profit is one of the key performance indicators of the company and each company needs to allocate resources in such a way that it achieves the greatest possible profit. The profit maximization problem is typically a dynamic optimization problem. This paper considers an approach to solving the problem of expanding production, using methods of Reinforcement Learning. The goal is to choose the firm's strategy for the long term: how to use the resources to maximize profits in the long-term period. To make the problem realistic, we consider the case of unstable demand. We study applicability of machine learning methods to optimal control problems, in particular Reinforcement Learning (RL), to optimal control problems arising in economics. To confirm or refute this possibility, we compare the analytical solution to the problem and the estimate obtained using the RL algorithms.