Markov Blanket

A Markov blanket is a minimal set of variables that renders a target variable conditionally independent of all other variables. Research focuses on efficiently identifying these blankets, particularly within complex systems like large-scale distributed computing environments and high-dimensional datasets, often employing algorithms adapted from Bayesian networks and reinforcement learning. Current efforts involve developing scalable methods for Markov blanket identification and leveraging this concept to improve the efficiency of machine learning models, causal inference, and the design of intelligent systems. This work has implications for diverse fields, including improving the scalability and explainability of reinforcement learning and enabling more efficient data processing in large-scale systems.

Papers

November 17, 2023

Designing Reconfigurable Intelligent Systems with Markov Blankets
Boris Sedlak, Victor Casamayor Pujol, Praveen Kumar Donta, Schahram Dustdar
Reconfigurable Intelligent Decentralized Artificial Intelligence Markov Blanket Continuum Tip Visual Causality Discovery

October 10, 2023

Scalable Semantic Non-Markovian Simulation Proxy for Reinforcement Learning
Kaustuv Mukherji, Devendra Parkar, Lahari Pokala, Dyuman Aditya, Paulo Shakarian, Clark Dorman
Reinforcement Learning Non Markovian Temporal Extension Markov Blanket Feature Proxy TransformeR

September 12, 2023

Learning Minimalistic Tsetlin Machine Clauses with Markov Boundary-Guided Pruning
Ole-Christoffer Granmo, Per-Arne Andersen, Lei Jiao, Xuan Zhang, Christian Blakely, Tor Tveit
Edge Pruning Markov Chain Tsetlin Machine Markov Model Markov Blanket Context Specific Independence

July 1, 2023

Causal Structure Learning by Using Intersection of Markov Blankets
Yiran Dong, Chuanhou Gao
Structural Causal Model Bayesian Network Intersection Scenario Causal Structure Learning Markov Blanket Exogenous Global Markov Process

October 21, 2022

BlanketGen - A synthetic blanket occlusion augmentation pipeline for MoCap datasets
João Carmona, Tamás Karácsony, João Paulo Silva Cunha
Human Pose Human Motion Analysis Markov Blanket Occlusion Augmentation

October 7, 2022

BlanketSet -- A clinical real-world in-bed action recognition and qualitative semi-synchronised MoCap dataset
João Carmona, Tamás Karácsony, João Paulo Silva Cunha
Computer Vision Action Recognition Human Motion Analysis Marker Less Mocap Markov Blanket Bed Human

May 6, 2022

Structure Learning in Graphical Models from Indirect Observations
Hang Zhang, Afshin Abdi, Faramarz Fekri
Graphical Model Structure Learning Dimensional Random Vector Graphical Structure Markov Blanket

April 29, 2022

Markov Abstractions for PAC Reinforcement Learning in Non-Markov Decision Processes
Alessandro Ronca, Gabriel Paludo Licks, Giuseppe De Giacomo
Markov Decision Process Markov Blanket

December 26, 2021

Reducing Planning Complexity of General Reinforcement Learning with Non-Markovian Abstractions
Sultan J. Majeed, Marcus Hutter
Reinforcement Learning Near Optimal Policy Diverse Planning Markov Blanket

Markov Blanket

Papers

Designing Reconfigurable Intelligent Systems with Markov Blankets

Scalable Semantic Non-Markovian Simulation Proxy for Reinforcement Learning

Learning Minimalistic Tsetlin Machine Clauses with Markov Boundary-Guided Pruning

Causal Structure Learning by Using Intersection of Markov Blankets

BlanketGen - A synthetic blanket occlusion augmentation pipeline for MoCap datasets

BlanketSet -- A clinical real-world in-bed action recognition and qualitative semi-synchronised MoCap dataset

Structure Learning in Graphical Models from Indirect Observations

Markov Abstractions for PAC Reinforcement Learning in Non-Markov Decision Processes

Reducing Planning Complexity of General Reinforcement Learning with Non-Markovian Abstractions