Innovations in the Field of On-Board Scheduling Technologies

Space missions are characterized by long distances, difficult or unavailable communication and high operating costs. Moreover, complexity has been constantly increasing in recent years. For this reason, improving the autonomy of space operators is an attractive goal to increase the mission reward with lower costs. This paper proposes an onboard scheduler, that integrates inside an onboard software framework for mission autonomy. Given a set of activities, it is responsible for determining the starting time of each activity according to their priority, order constraints, and resource consumption. The presented scheduler is based on linear integer programming and relies on the use of a branch-and-cut solver. The technology has been tested on an Earth Observation scenario, comparing its performance against the state-of-the-art scheduling technology

An AI-Based Goal-Oriented Agent for Advanced On-Board Automation

In the context of fierce competition arising in the space economy, the number of satellites and constellations that will be placed in orbit is set to increase considerably in the upcoming years. In such a dynamic environment, raising the autonomy level of the next space missions is key to maintaining a competitive edge in terms of the scientific, technological, and commercial outcome. We propose the adoption of an AI-based autonomous agent aiming to fully enable spacecraft’s goal-oriented autonomy. The implemented cognitive architecture collects input starting from the sensing of the surrounding operating environment and defines a low-level schedule of tasks that will be carried out throughout the specified horizon. Furthermore, the agent provides a planner module designed to find optimal solutions that maximize the outcome of the pursued objective goal. The autonomous loop is closed by comparing the expected outcome of these scheduled tasks against the real environment measurements. The entire algorithmic pipeline was tested in a simulated operational environment, specifically developed for replicating inputs and resources relative to Earth Observation missions. The autonomous reasoning agent was evaluated against the classical, non-autonomous, mission control approach, considering both the quantity and the quality of collected observation data in addition to the quantity of the observation opportunities exploited throughout the simulation time. The preliminary simulation results point out that the adoption of our software agent enhances dramatically the effectiveness of the entire mission, increasing and optimizing in-orbit activities, on the one hand, reducing events\u27 response latency (opportunities, failures, malfunctioning, etc.) on the other. In the presentation, we will cover the description of the high-level algorithmic structure of the proposed goal-oriented reasoning model, as well as a brief explanation of each internal module’s contribution to the overall agent’s architecture. Besides, an overview of the parameters processed as input and the expected algorithms\u27 output will be provided, to contextualize the placement of the proposed solution. Finally, an Earth Observation use case will be used as the benchmark to test the performances of the proposed approach against the classical one, highlighting promising conclusions regarding our autonomous agent’s adoption

The role of prepayment penalties in mortgage loans

We study the effect of mortgage prepayment penalties on borrowers’ prepayments and delinquencies by exploiting a 2007 reform in Italy that reduced penalties on outstanding mortgages and banned penalties on newly-issued mortgages. Using a unique dataset of mortgages issued by a large Italian lender, we provide evidence that: 1) before the reform, mortgages issued to riskier borrowers included larger penalties; 2) higher prepayment penalties decreased borrowers’ prepayments; and 3) higher prepayment penalties did not affect borrowers’ delinquencies. Moreover, we find suggestive evidence that prepayment penalties affected mortgage pricing, as well as prepayments and delinquencies through borrowers’ mortgage selection at origination, most notably for riskier borrowers

Conoscenza, cura dei luoghi e partecipazione come opportunit\ue0 di sviluppo dell'umano e promozione di competenze di cittadinanza

Il contributo sviluppa il significato di sviluppo di competenze di cittadinanza sostenibile e presa in cura dei luoghi all'interno di percorsi progettuali di Outdoor Education, che trovano cos\uec un loro costrutto pedagogico-epistemologico