Fast local search methods for solving limited memory influence diagrams

DOI10.1016/j.ijar.2015.05.003zbMath1346.68178OpenAlexW341277852WikidataQ62046524 ScholiaQ62046524MaRDI QIDQ895537

Denis Deratani Mauá, Fabio Gagliardi Cozman

Publication date: 3 December 2015

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2015.05.003

zbMATH Keywords

decision makinglocal searchinfluence diagramsprobabilistic graphical modelsparameterized complexity

Mathematics Subject Classification ID

Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20) Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.) (68Q17)

Related Items (2)

On Imperfect Recall in Multi-Agent Influence Diagrams ⋮ Strategy Graphs for Influence Diagrams

Uses Software

• ElemStatLearn
• k-Neighborhood
• Hailfinder

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• The parameterized complexity of \(k\)-flip local search for SAT and MAX SAT
• On the complexity of solving polytree-shaped limited memory influence diagrams with binary variables
• Fixed-parameter tractability and completeness II: On completeness for W[1]
• A computational theory of decision networks
• On the hardness of approximate reasoning
• Solving Limited Memory Influence Diagrams
• The Necessity of Bounded Treewidth for Efficient Inference in Bayesian Networks
• Representing and Solving Decision Problems with Limited Information
• Dynamic programming and influence diagrams
• Bayesian Networks and Decision Graphs
• Probabilistic Networks and Expert Systems
• Fixed-Parameter Tractability and Completeness I: Basic Results

This page was built for publication: Fast local search methods for solving limited memory influence diagrams