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Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes

2016

Conference Paper

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Information-theoretic principles for learning and acting have been proposed to solve particular classes of Markov Decision Problems. Mathematically, such approaches are governed by a variational free energy principle and allow solving MDP planning problems with information-processing constraints expressed in terms of a Kullback-Leibler divergence with respect to a reference distribution. Here we consider a generalization of such MDP planners by taking model uncertainty into account. As model uncertainty can also be formalized as an information-processing constraint, we can derive a unified solution from a single generalized variational principle. We provide a generalized value iteration scheme together with a convergence proof. As limit cases, this generalized scheme includes standard value iteration with a known model, Bayesian MDP planning, and robust planning. We demonstrate the benefits of this approach in a grid world simulation.

Author(s): Grau-Moya, J and Leibfried, F and Genewein, T and Braun, DA
Book Title: Machine Learning and Knowledge Discovery in Databases
Pages: 475-491
Year: 2016
Month: September
Series: Lecture Notes in Computer Science; 9852
Publisher: Springer

Department(s): Empirische Inferenz
Bibtex Type: Conference Paper (conference)

DOI: 10.1007/978-3-319-46227-1_30
Event Name: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML PKDD 2016)
Event Place: Riva del Garda, Italy

Address: Cham, Switzerland
State: Published

BibTex

@conference{GrauMoyaLGB2016,
  title = {Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes},
  author = {Grau-Moya, J and Leibfried, F and Genewein, T and Braun, DA},
  booktitle = {Machine Learning and Knowledge Discovery in Databases},
  pages = {475-491},
  series = {Lecture Notes in Computer Science; 9852},
  publisher = {Springer},
  address = {Cham, Switzerland},
  month = sep,
  year = {2016},
  month_numeric = {9}
}