Causal Graph Based Dynamic Optimization of Hierarchies for Factored MDPs

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Wang:2012:WI-IAT,
  author =       "Hongbing Wang and Jiancai Zhou and Xuan Zhou",
  booktitle =    "IEEE/WIC/ACM International Conferences on Web
                 Intelligence and Intelligent Agent Technology (WI-IAT
                 2012)",
  title =        "Causal Graph Based Dynamic Optimization of Hierarchies
                 for Factored MDPs",
  year =         "2012",
  volume =       "1",
  pages =        "579--582",
  month =        "4-7 " # dec,
  address =      "Macau, China",
  isbn13 =       "978-1-4673-6057-9",
  DOI =          "doi:10.1109/WI-IAT.2012.59",
  size =         "4 pages",
  abstract =     "This paper presents an approach based on casual graph
                 to optimise the task hierarchies for Hierarchical
                 Reinforcement Learning (HRL). We conducted experiments
                 to show that the resulting task hierarchies can improve
                 effectiveness of reinforcement leaning.",
  keywords =     "genetic algorithms, genetic programming, Complex
                 systems, casual graph, hierarchical reinforcement
                 learning",
  notes =        "Also known as \cite{6511944}",
}

Genetic Programming entries for Hongbing Wang Jiancai Zhou Xuan Zhou

Citations