Towards Interpretable-AI Policies Induction using Evolutionary Nonlinear Decision Trees for Discrete Action Systems

20 September 2020

Papers citing "Towards Interpretable-AI Policies Induction using Evolutionary Nonlinear Decision Trees for Discrete Action Systems"

6 / 6 papers shown

Title
Explaining Deep Convolutional Neural Networks for Image Classification by Evolving Local Interpretable Model-agnostic Explanations Bin Wang Wenbin Pei Bing Xue Mengjie Zhang FAtt 36 3 0 28 Nov 2022
Fast Optimization of Weighted Sparse Decision Trees for use in Optimal Treatment Regimes and Optimal Policy Design Ali Behrouz Mathias Lécuyer Cynthia Rudin Margo Seltzer OffRL 28 2 0 13 Oct 2022
Quality Diversity Evolutionary Learning of Decision Trees Andrea Ferigo Leonardo Lucio Custode Giovanni Iacca 43 12 0 17 Aug 2022
Interpretable pipelines with evolutionarily optimized modules for RL tasks with visual inputs Leonardo Lucio Custode Giovanni Iacca 27 13 0 10 Feb 2022
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 59 655 0 20 Mar 2021
Particle Swarm Optimization for Generating Interpretable Fuzzy Reinforcement Learning Policies D. Hein A. Hentschel Thomas Runkler Steffen Udluft OffRL 28 79 0 19 Oct 2016