We prove that binary decision diagrams [1] can be polynomially simulated by the extended resolution rule of [2]. More precisely, for any unsatisfiable formula , there exists an ex...
Decision trees are a widely used knowledge representation in machine learning. However, one of their main drawbacks is the inherent replication of isomorphic subtrees, as a result...
Christophe Mues, Bart Baesens, Craig M. Files, Jan...
Decision diagrams are the state-of-the-art representation for logic functions, both binary and multiple-valued. Here we consider ways to improve the construction of multiple-value...
Recently, a number of works have been published on implementing assignment decision diagram models combined with SAT methods to address register-transfer level test pattern genera...
Dynamic programming algorithms provide a basic tool identifying optimal solutions in Markov Decision Processes (MDP). The paper develops a representation for decision diagrams sui...