Encoding and rewriting of large set of terms is very useful in a number of domains, such as model checking and theorem proving. The challenge of encoding and normalizing several billions of terms requires efficient ways of representing and manipulating them. Term Graph Rewriting is a well-known technique to share common sub-terms and thus to save both memory and processing time. However, this does not always fit well to the operational framework since it destroys the original structure and replaces it by a new one. This paper introduces a new kind of Decision Diagrams (DD), especially designed to handle set of terms in an efficient way. Based on the Set Decision Diagrams(SDD), an evolution of the well-known Binary Decision Diagrams(BDD), we...
Binary Decision Diagrams (BDDs) [1] and their variations are a known representation of Boolean funct...
The Sentential Decision Diagram (SDD) is a prominent knowledge representation language that subsumes...
Decision trees are a widely used knowledge representation in machine learn-ing. However, one of thei...
In this thesis we tackle the difficulty of translating a high level formalism to Decision Diagrams (...
In this paper we propose a uniform description of basic BDD theory and algorithms by means of term r...
AbstractBinary decision diagrams (BDDs) provide an established technique for propositional formula m...
In this thesis we tackle the difficulty of translating a high level formalism to Decision Diagrams (...
BDDs provide an established technique for propositional formula ma-nipulation. In this paper we pres...
Abstract. Decision Diagrams (DDs) are a well populated family of data structures, used for efficient...
International audienceShared decision diagram representations of a state-space have been shown to pr...
Abstract. Symbolic model-checking using binary decision diagrams (BDD) can allow to represent very l...
Decision trees are a widely used knowledge representation in machine learning. However, one of their...
The Sentential Decision Diagram (SDD) is a recently proposed representation of Boolean functions, co...
International audienceDecision diagrams (DD) present a suitable way for the digital system represent...
International audienceShared decision diagram representations of a state-space provide efficient sol...
Binary Decision Diagrams (BDDs) [1] and their variations are a known representation of Boolean funct...
The Sentential Decision Diagram (SDD) is a prominent knowledge representation language that subsumes...
Decision trees are a widely used knowledge representation in machine learn-ing. However, one of thei...
In this thesis we tackle the difficulty of translating a high level formalism to Decision Diagrams (...
In this paper we propose a uniform description of basic BDD theory and algorithms by means of term r...
AbstractBinary decision diagrams (BDDs) provide an established technique for propositional formula m...
In this thesis we tackle the difficulty of translating a high level formalism to Decision Diagrams (...
BDDs provide an established technique for propositional formula ma-nipulation. In this paper we pres...
Abstract. Decision Diagrams (DDs) are a well populated family of data structures, used for efficient...
International audienceShared decision diagram representations of a state-space have been shown to pr...
Abstract. Symbolic model-checking using binary decision diagrams (BDD) can allow to represent very l...
Decision trees are a widely used knowledge representation in machine learning. However, one of their...
The Sentential Decision Diagram (SDD) is a recently proposed representation of Boolean functions, co...
International audienceDecision diagrams (DD) present a suitable way for the digital system represent...
International audienceShared decision diagram representations of a state-space provide efficient sol...
Binary Decision Diagrams (BDDs) [1] and their variations are a known representation of Boolean funct...
The Sentential Decision Diagram (SDD) is a prominent knowledge representation language that subsumes...
Decision trees are a widely used knowledge representation in machine learn-ing. However, one of thei...