In this work we analyze and implement different Reinforcement Learning (RL) algorithms in financial trading system applications. RL-based algorithms applied to financial systems aim to find an optimal policy, that is an optimal mapping between the variables describing the state of the system and...

This paper proposes a simple procedure, in order to aggregate a nite number of real nonnegative values into a unique indicator. Possible applications of this tool can be found in social sciences, including demography, sociology, etc. In particular, the indicator may represent a generalized mean,...

In this work we use a MultiCriteria Decision Analysis (MCDA) model to evaluate the creditworthiness of a sample of Italian Small and Medium-sized Enterprises (SMEs), on the basis of their balance sheet data provided by the AIDA database. Our methodology is able to consider simultaneously...

In this paper we propose an efficient initialization of a deterministic Particle Swarm Optimization (PSO) scheme. PSO has showed to be promising for solving several unconstrained global optimization problems from real applications, where derivatives are unavailable and the evaluation of the...

In this paper we introduce a parameter dependent class of Krylov-based methods, namely CD, for the solution of symmetric linear systems. We give evidence that in our proposal we generate sequences of conjugate directions, extending some properties of the standard Conjugate Gradient (CG) method,...

We consider the problem of measuring the performances associated with members of a given group of homogeneous individuals. We provide both an analysis, relying on Machine Learning paradigms, along with a numerical experience based on three conceptually different real applications. A keynote...