CP was co-located with ICAPS, KR, and NMR; see below.

Invited speakers

Alain Colmerauer, France Back to the Complexity of Universal Programs

The talk discusses a framework enabling one to define and determine the complexity of various universal programs U for various machines. The approach consists of first defining the complexity as the average number of instructions to be executed by U, when simulating the execution of one instruction of a program P with input x. To obtain a complexity that does not depend on P or x, we introduce the concept of an introspection coefficient expressing the average number of instructions executed by U, for simulating the execution of one of its own instructions. We show how to obtain this coefficient by computing a square matrix whose elements are numbers of executed instructions when running selected parts of U on selected data. The coefficient then becomes the greatest eigenvalue of the matrix. We illustrate the approach using two examples of particularly efficient universal programs: one for a three-symbol Turing Machine (blank symbol not included) with an introspection coefficient of 3672.98, the other for an indirect addressing arithmetic machine with an introspection coefficient of 26.27.

Adnan Darwiche, University of California, USA (jointly with KR) Satisfiability, Knowledge Compilation and the Journey Towards Universal Reasoning Engines

The development of universal reasoning engines has been a main objective of AI since its very early days. The vision here is to relief system developers from having to worry about reasoning algorithms, focusing only on capturing the necessary knowledge, while delegating algorithmic considerations to these engines. Few decades after this original vision was first conceived, the field of AI is starting to bear its fruits, initially through SAT solvers, and more recently through knowledge compilers (and related model counters).

In this talk, I will discuss some of the progress in realizing this vision, highlighting both successes and missed opportunities. For example, on the satisfiability front, I will present a semantics for modern SAT solvers, which is somewhat distant from how these solvers are commonly understood. I will argue that the lack of this and similar semantics could be the reason behind the lack of recent leaps in SAT solving, which have been saught after since the zchaff solver was introduced many years ago. On the knowledge compilation front, I will review some of the key advancements, especially in relation to SAT solving and model counting, and point to some of the major gaps between what the theory says is possible and what current practice allows. I will argue that bridging this gap requires some novelties, especially in how systematic search is currently practiced. I will also discuss some recent breakthroughs that seem to have brought us closer to bridging this gap.

John Hooker, Carnegie Mellon University, USA (jointly with ICAPS) How to Relax

Relaxation is a theme that occurs in many problem solving methods. It is often associated with optimization, but relaxation plays an equally important role in finite-domain constraint programming and other discrete methods. This talk surveys a wide variety of relaxation methods, including linear relaxation and cutting planes, Lagrangean relaxation, the domain store and related relaxations, state space relaxation, relaxations in decomposition methods, as well as nonserial dynamic programming, mini buckets, and other relaxations based on simplifying the primal graph. Recognizing the role of relaxation can suggest improvements based on strengthening the relaxation. Consistency maintenance, for example, in effect strengthens relaxations. Other approaches include the use of such knowledge compilation devices as and/or trees and multivalued decision diagrams, and the solution of a relaxation dual problem.


Javier Larrosa: Current issues on Max-SAT

Propositional satifiability (SAT) is a research field strongly related to CP. SAT solvers have improved dramatically in the last years and are currently used to solve problems in many industrial applications. The main reasons for this success are the use of an extremely simple language (CNF) for which solvers can be highly optimized. The success story of SAT solvers has led to the study of several extensions of propositional logic, and Max-SAT is arguably the most prominent one. In short, Max-SAT is the natural extension of SAT to model and solve optimization problems (in contrast to decision problems). It has attracted a lot of interest and, only from the work done in the last 5 years, current solvers outperform previous ones by several orders of magnitude. The purpose of the tutorial is to overview this recent research with special emphasis in the algorithmic aspects and its potential applications. The tutorial will cover with unified notation the essential ideas behind modern solvers.

Didier Vidal: ILOG CP Optimizer: An Automatic Search and Modeling Framework for Detailed Scheduling

In this software tutorial we present a modeling framework and automatic search for detailed scheduling problems. We describe a new modeling framework based on a compact set of algebraic concepts that can be used to model a wide variety of hard and soft scheduling problems, while taking advantage of work breakdown structures. Together with a tunable search engine, models can be simply run and solved with default settings or with adjusted engine parameters and declarative search phases, to rapidly produce quality schedules.

Doctoral Program

See the CP DP page for detailed information.


CP-WS1: Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS'08) (jointly with ICAPS)

CP-WS2: Counting Problems in CSP and SAT, and Other Neighbouring Problems (Counting'08)

CP-WS3: Local Search Techniques in Constraint Satisfaction (LSCS'08)

CP-WS4: Constraint Modelling and Reformulation (ModRef'08)

CP-WS6: Preferences and Soft Constraints (SofT'08)

CP-WS7: Symmetry and Constraint Satisfaction Problems (SymCon'08)

CP-WS8: Quantification in Constraint Programming (QiCP'08)

CP-WS9: CSP Solver Competition

(Cancelled: CP-WS5: Search in ManyCore)

Co-located events

Delegates attending the CP conference were able to attend the sessions of

which ran alongside it. The single registration fee granted attendance to research paper presentations, tutorials and workshops of these co-located events. Some sessions were shared.

Not co-located but taking place temporally and geographically close were the following events: the International Joint Conference on Automated Reasoning (IJCAR) took place in Sydney during 10–15 August, and the International Workshop on Principles of Diagnosis (DX) took place near Sydney in the week following CP.

Conference Dinner

The joint Conference Dinner took place on board MV Sydney 2000 on Wednesday night. (Please see the program or local information for details.)