3 papers
eess.SY2023
Exact hierarchical reductions of dynamical models via linear transformations
Alexander Demin, Elizaveta Demitraki, Gleb Pogudin
Dynamical models described by ordinary differential equations (ODEs) are a fundamental tool in the sciences and engineering. Exact reduction aims at producing a lower-dimensional m…
cs.AI2022
Machine Learning with Probabilistic Law Discovery: A Concise Introduction
Alexander Demin, Denis Ponomaryov
Probabilistic Law Discovery (PLD) is a logic based Machine Learning method, which implements a variant of probabilistic rule learning. In several aspects, PLD is close to Decision…
cs.AI2022
Interpretable Reinforcement Learning with Multilevel Subgoal Discovery
Alexander Demin, Denis Ponomaryov
We propose a novel Reinforcement Learning model for discrete environments, which is inherently interpretable and supports the discovery of deep subgoal hierarchies. In the model, a…