Sökning: "Giorgio Sacchi"

Hittade 2 uppsatser innehållade orden Giorgio Sacchi.

  1. 1. Computationally Efficient Explainable AI: Bayesian Optimization for Computing Multiple Counterfactual Explanantions

    Master-uppsats, KTH/Matematik (Avd.)

    Författare :Giorgio Sacchi; [2023]
    Nyckelord :Explainable AI; Counterfactual Explanations CFEs ; Bayesian Optimization BO ; Black-Box Models; Model-Agnostic; Machine Learning ML ; Efficient Computation; High-Stake Decisions; Förklarbar AI; Kontrafaktuell Förklaring CFE ; Bayesiansk Optimering BO ; Svarta lådmodeller; Modellagnostisk; Maskininlärning; Beräkningsmässigt Effektiv; Beslut med höga insatser;

    Sammanfattning : In recent years, advanced machine learning (ML) models have revolutionized industries ranging from the healthcare sector to retail and E-commerce. However, these models have become increasingly complex, making it difficult for even domain experts to understand and retrace the model's decision-making process. LÄS MER

  3. 2. En spelteoretisk AI för Stratego

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Giorgio Sacchi; David Bardvall; [2021]
    Nyckelord :Counterfactual Regret Minimization; AI; Imperfect recall; Wargames; Imperfect infomation games; Stratego;

    Sammanfattning : Many problems involving decision making withimperfect information can be modeled as extensive games. Onefamily of state-of-the-art algorithms for computing optimal playin such games is Counterfactual Regret Minimization (CFR).The purpose of this paper is to explore the viability of CFRalgorithms on the board game Stratego. LÄS MER