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cs.PL2025
Rulebook: bringing co-routines to reinforcement learning environments
Massimo Fioravanti, Samuele Pasini, Giovanni Agosta
Reinforcement learning (RL) algorithms, due to their reliance on external systems to learn from, require digital environments (e.g., simulators) with very simple interfaces, which…
cs.PL2022★ 3 cited
Array-Aware Matching: Taming the Complexity of Large-Scale Simulation Models
Massimo Fioravanti, Daniele Cattaneo, Federico Terraneo +5
Equation-based modelling is a powerful approach to tame the complexity of large-scale simulation problems. Equation-based tools automatically translate models into imperative langu…