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Influence of modeling structure in probabilistic sequential decision problems

Florent Teichteil-Königsbuch, Patrick Fabiani (2006)

RAIRO - Operations Research

Markov Decision Processes (MDPs) are a classical framework for stochastic sequential decision problems, based on an enumerated state space representation. More compact and structured representations have been proposed: factorization techniques use state variables representations, while decomposition techniques are based on a partition of the state space into sub-regions and take advantage of the resulting structure of the state transition graph. We use a family of probabilistic exploration-like...

Integer partitions, tilings of 2 D -gons and lattices

Matthieu Latapy (2002)

RAIRO - Theoretical Informatics and Applications - Informatique Théorique et Applications

In this paper, we study two kinds of combinatorial objects, generalized integer partitions and tilings of 2 D -gons (hexagons, octagons, decagons, etc.). We show that the sets of partitions, ordered with a simple dynamics, have the distributive lattice structure. Likewise, we show that the set of tilings of a 2 D -gon is the disjoint union of distributive lattices which we describe. We also discuss the special case of linear integer partitions, for which other dynamical models exist.

Integer Partitions, Tilings of 2D-gons and Lattices

Matthieu Latapy (2010)

RAIRO - Theoretical Informatics and Applications

In this paper, we study two kinds of combinatorial objects, generalized integer partitions and tilings of 2D-gons (hexagons, octagons, decagons, etc.). We show that the sets of partitions, ordered with a simple dynamics, have the distributive lattice structure. Likewise, we show that the set of tilings of a 2D-gon is the disjoint union of distributive lattices which we describe. We also discuss the special case of linear integer partitions, for which other dynamical models exist.

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