An integrated approach to solving influence diagrams and finite-horizon partially observable decision processes

DOI10.1016/j.artint.2020.103431OpenAlexW3109500076MaRDI QIDQ2238620

Eric A. Hansen

Publication date: 2 November 2021

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.artint.2020.103431

zbMATH Keywords

dynamic programmingvariable eliminationpartially observable Markov decision processdecision-theoretic planninginfluence diagram

Mathematics Subject Classification ID

Artificial intelligence (68Txx)

Related Items (1)

Strategy Graphs for Influence Diagrams

Uses Software

• NMRDPP

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Planning and acting in partially observable stochastic domains
• A survey of solution techniques for the partially observed Markov decision process
• Equivalences between maximum a posteriori inference in Bayesian networks and maximum expected utility computation in influence diagrams
• Variable elimination for influence diagrams with super value nodes
• Potential influence diagrams
• Stochastic dynamic programming with factored representations
• Evaluating interval-valued influence diagrams
• A survey of algorithmic methods for partially observed Markov decision processes
• Markov decision processes with noise-corrupted and delayed state observations
• Dynamic programming and influence diagrams
• Bayesian Networks and Decision Graphs
• State of the Art—A Survey of Partially Observable Markov Decision Processes: Theory, Models, and Algorithms
• Valuation-Based Systems for Bayesian Decision Analysis
• Probabilistic Networks and Expert Systems
• The Optimal Control of Partially Observable Markov Processes over a Finite Horizon
• Markov decision processes with delays and asynchronous cost collection
• Probabilistic decision graphs for optimization under uncertainty
• Improvements to variable elimination and symbolic probabilistic inference for evaluating influence diagrams

This page was built for publication: An integrated approach to solving influence diagrams and finite-horizon partially observable decision processes