Recently, increased computational power and data availability, as well as algorithmic
advances, have led machine learning (ML) techniques to impressive results in regression …

This book is rooted in the thesis that complexity theory is extremely rich in conceptual
content, and that this contents should be explicitly communicated in expositions and courses …

“Satisfiability (SAT) related topics have attracted researchers from various disciplines: logic,
applied areas such as planning, scheduling, operations research and combinatorial …

Boolean functions are perhaps the most basic objects of study in theoretical computer
science. They also arise in other areas of mathematics, including combinatorics, statistical …

Constraint programming is a powerful paradigm for solving combinatorial search problems
that draws on a wide range of techniques from artificial intelligence, computer science …

Written by prominent experts in the field, this monograph provides the first comprehensive,
unified presentation of the structural, algorithmic and applied aspects of the theory of …

Many natural combinatorial problems can be expressed as constraint satisfaction problems.
This class of problems is known to be NP-complete in general, but certain restrictions on the …

In this paper we describe a method that estimates the motion of a calibrated camera (settled
on an experimental vehicle) and the tridimensional geometry of the environment. The only …

Feature models are a popular variability modeling notation used in product line engineering.
Automated analyses of feature models, such as consistency checking and interactive or …

We introduce an efficient method for translating planning tasks specified in the standard
PDDL formalism into a concise grounded representation that uses finite-domain state …