Silviatulli

aceirl

Implementation of "Active Exploration for Inverse Reinforcement Learning (AceIRL), NeurIPS 2022.

altermax

two-agents setting with minmax planner for counterfactual explanations - Learning from Explanations and Demonstrations: A Pilot Study

contrastive_examples_MLIRL

Codes to reproduce the results of the paper Contrastive Examples in Maximum Likelihood Inverse Reinforcement Learning

dyadic-minigrid

multiplayer game and chat for collecting data on human counterfactual explanations in a collaborative learning task

IN_104-Projet-Informatique

This is the website of the Computer Science Project course on Genetic Algorithms

Python-Print-Booklet

It is Python script able to impose a single page pdf into ready-to-print booklet.

RLhomework

multi-armed bandit, gambler problem, cliff problem and TD learning

single-machine-scheduling

software tool for solving a single machine scheduling (SMS) problem using a MiniZinc framework for constraint satisfaction problems (CSP)

suboptimax

minmax planner for suboptimal explanations - Explainable Agency by Revealing Suboptimality in CHRI Learning Scenarios

XAI-tutorial

A comprehensive set of colab notebooks to showcase the principal differences among XAI techniques

Silviatulli/altermax

two-agents setting with minmax planner for counterfactual explanations - Learning from Explanations and Demonstrations: A Pilot Study

Silviatulli/IN_104-Projet-Informatique

This is the website of the Computer Science Project course on Genetic Algorithms

Silviatulli/RLhomework

multi-armed bandit, gambler problem, cliff problem and TD learning

Silviatulli/XAI-tutorial

A comprehensive set of colab notebooks to showcase the principal differences among XAI techniques

Silviatulli/aceirl

Implementation of "Active Exploration for Inverse Reinforcement Learning (AceIRL), NeurIPS 2022.

Silviatulli/awesome-explanatory-supervision

List of relevant resources for machine learning from explanatory supervision

Silviatulli/contrastive_examples_MLIRL

Codes to reproduce the results of the paper Contrastive Examples in Maximum Likelihood Inverse Reinforcement Learning

Silviatulli/dyadic-minigrid

multiplayer game and chat for collecting data on human counterfactual explanations in a collaborative learning task

Silviatulli/single-machine-scheduling

software tool for solving a single machine scheduling (SMS) problem using a MiniZinc framework for constraint satisfaction problems (CSP)

Silviatulli/suboptimax

minmax planner for suboptimal explanations - Explainable Agency by Revealing Suboptimality in CHRI Learning Scenarios

Silviatulli/BCI_Matlab

Brain-Computer Interface - data analysis, k nearest neighbors classifier

Silviatulli/gpairls

Generalizing Persistent Advice in Interactive Reinforcement Learning Scenarios

Silviatulli/imitation

Clean PyTorch implementations of imitation and reward learning algorithms

Silviatulli/learnermax

minmax planner for suboptimal explanations with POMDP framework to optimize those explanations for the learner level of expertise

Silviatulli/LOGEL

Inverse Reinforcement Learning from a Gradient-based Learner

Silviatulli/MachineLearningPython

collections of vanilla ML models implemented with existing python libraries and simple datasets

Silviatulli/meta-learning-curiosity-algorithms

Silviatulli/py_courses

Collection of Python classes

Silviatulli/rl-baselines3-zoo

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

Silviatulli/RL4XAI

Sequential Explanations with Mental Model-Based Policies (Reinforcement Learning for Explainable AI)

Silviatulli/salina

a Lightweight library for sequential learning agents, including reinforcement learning

Silviatulli/silvia_grids

gym compatible customized gridworld environments

Silviatulli/Silviatulli

Config files for my GitHub profile.

Silviatulli/simple_MLwebapp

Introductory tutorial to build a Flask web application that integrates a machine learning model. The dummy example takes the mood and the hours of sleep of the user as a numerical input and predicts the workload in hours.

Silviatulli/StarCraft-II-causal-explanations

Silviatulli/time-series-forecasting-r

study example of time series forecasting with R

Silviatulli/transformers-interpret

Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

Silviatulli/XAI-tutorials

Silviatulli/XAI_transformer_tutorial

BERT SQUAD Interpret from Captum

Silviatulli/yaaf

Yet Another Agents Framework - An RL research-oriented framework for agent prototyping and evaluation