16 citations · 60 across the 12 of their papers we have counts for
10 papers · 1 filter
Scaling Neuro-symbolic Problem Solving: Solver-Free Learning of Constraints and Objectives
Marianne Defresne, Romain Gambardella, Sophie Barbe +1
In the ongoing quest for hybridizing discrete reasoning with neural nets, there is an increasing interest in neural architectures that can learn how to solve discrete reasoning or…
Scalable Coupling of Deep Learning with Logical Reasoning
Marianne Defresne, Sophie Barbe, Thomas Schiex
In the ongoing quest for hybridizing discrete reasoning with neural nets, there is an increasing interest in neural architectures that can learn how to solve discrete reasoning or…
Tractability and Decompositions of Global Cost Functions
David Allouche, Christian Bessiere, Patrice Boizumault +8
Enforcing local consistencies in cost function networks is performed by applying so-called Equivalent Preserving Transformations (EPTs) to the cost functions. As EPTs transform the…
Bounds Arc Consistency for Weighted CSPs
Matthias Zytnicki, Christine Gaspin, Simon de Givry +1
The Weighted Constraint Satisfaction Problem (WCSP) framework allows representing and solving problems involving both hard constraints and cost functions. It has been applied to va…
Possibilistic Constraint Satisfaction Problems or "How to handle soft constraints?"
Thomas Schiex
Many AI synthesis problems such as planning or scheduling may be modelized as constraint satisfaction problems (CSP). A CSP is typically defined as the problem of finding any consi…
Penalty logic and its Link with Dempster-Shafer Theory
Florence Dupin de Saint-Cyr, Jerome Lang, Thomas Schiex
Penalty logic, introduced by Pinkas, associates to each formula of a knowledge base the price to pay if this formula is violated. Penalties may be used as a criterion for selecting…