Minimum Cardinality Matrix Decomposition into Consecutive-Ones Matrices: CP and IP Approaches.- Connections in Networks: Hardness of Feasibility Versus Optimality.- Modeling the Regular Constraint with Integer Programming.- Hybrid Local Search for Constrained Financial Portfolio Selection Problems.- The "Not-Too-Heavy Spanning Tree" Constraint.- Eliminating Redundant Clauses in SAT Instances.- Cost-Bounded Binary Decision Diagrams for 0-1 Programming.- YIELDS: A Yet Improved Limited Discrepancy Search for CSPs.- A Global Constraint for Total Weighted Completion Time.- Computing Tight Time Windows for RCPSPWET with the Primal-Dual Method.- Necessary Condition for Path Partitioning Constraints.- A Constraint Programming Approach to the Hospitals / Residents Problem.- Best-First AND/OR Search for 0/1 Integer Programming.- A Position-Based Propagator for the Open-Shop Problem.- Directional Interchangeability for Enhancing CSP Solving.- A Continuous Multi-resources cumulative Constraint with Positive-Negative Resource Consumption-Production.- Replenishment Planning for Stochastic Inventory Systems with Shortage Cost.- Preprocessing Expression-Based Constraint Satisfaction Problems for Stochastic Local Search.- The Deviation Constraint.- The Linear Programming Polytope of Binary Constraint Problems with Bounded Tree-Width.- On Boolean Functions Encodable as a Single Linear Pseudo-Boolean Constraint.- Solving a Stochastic Queueing Control Problem with Constraint Programming.- Constrained Clustering Via Concavity Cuts.- Bender's Cuts Guided Large Neighborhood Search for the Traveling Umpire Problem.- A Large Neighborhood Search Heuristic for Graph Coloring.- Generalizations of the Global Cardinality Constraint for Hierarchical Resources.- A Column Generation Based Destructive Lower Bound for Resource Constrained Project Scheduling Problems.

Integration of AI and OR techniques in constraint programming for combinatorial optimization problems : 4th International Conference, CPAIOR 2007, Brussels, Belgium, May 23-26, 2007 : proceedings

This chapter describes Jason, an interpreter written in Java for an extended version of AgentSpeak, a logic-based agent-oriented programming language that is suitable for the implementation of reactive planning systems according to the BDI architecture. We describe both the language and the various features and tools available in the platform.

Jason and the Golden Fleece of agent-oriented programming.

Invited Papers- Global Optimization of Probabilistically Constrained Linear Programs- Algorithms and Constraint Programming- Interval Analysis and Robotics- Constraint Based Resilience Analysis- Regular Papers- Infinite Qualitative Simulations by Means of Constraint Programming- Algorithms for Stochastic CSPs- Graph Properties Based Filtering- The ROOTS Constraint- CoJava: Optimization Modeling by Nondeterministic Simulation- An Algebraic Characterisation of Complexity for Valued Constraint- Typed Guarded Decompositions for Constraint Satisfaction- Propagation in CSP and SAT- The Minimum Spanning Tree Constraint- Impact of Censored Sampling on the Performance of Restart Strategies- Watched Literals for Constraint Propagation in Minion- Inner and Outer Approximations of Existentially Quantified Equality Constraints- Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms- Adaptive Clause Weight Redistribution- Localization of an Underwater Robot Using Interval Constraint Propagation- Approximability of Integer Programming with Generalised Constraints- When Constraint Programming and Local Search Solve the Scheduling Problem of Electricite de France Nuclear Power Plant Outages- Generalized Arc Consistency for Positive Table Constraints- Stochastic Allocation and Scheduling for Conditional Task Graphs in MPSoCs- Boosting Open CSPs- Compiling Constraint Networks into AND/OR Multi-valued Decision Diagrams (AOMDDs)- Distributed Constraint-Based Local Search- High-Level Nondeterministic Abstractions in C++- A Structural Characterization of Temporal Dynamic Controllability- When Interval Analysis Helps Inter-block Backtracking- Randomization in Constraint Programming for Airline Planning- Towards an Efficient SAT Encoding for Temporal Reasoning- Decomposition of Multi-operator Queries on Semiring-Based Graphical Models- Dynamic Lex Constraints- Generalizing AllDifferent: The SomeDifferent Constraint- Mini-bucket Elimination with Bucket Propagation- Constraint Satisfaction with Bounded Treewidth Revisited- Preprocessing QBF- The Theory of Grammar Constraints- Constraint Programming Models for Graceful Graphs- A Simple Distribution-Free Approach to the Max k-Armed Bandit Problem- Generating Propagators for Finite Set Constraints- Compiling Finite Linear CSP into SAT- Differentiable Invariants- Revisiting the Sequence Constraint- BlockSolve: A Bottom-Up Approach for Solving Quantified CSPs- General Symmetry Breaking Constraints- Poster Papers- Inferring Variable Conflicts for Local Search- Reasoning by Dominance in Not-Equals Binary Constraint Networks- Distributed Stable Matching Problems with Ties and Incomplete Lists- Soft Arc Consistency Applied to Optimal Planning- A Note on Low Autocorrelation Binary Sequences- Relaxations and Explanations for Quantified Constraint Satisfaction Problems- Static and Dynamic Structural Symmetry Breaking- The Modelling Language Zinc- A Filter for the Circuit Constraint- A New Algorithm for Sampling CSP Solutions Uniformly at Random- Sports League Scheduling: Enumerative Search for Prob026 from CSPLib- Dynamic Symmetry Breaking Restarted- The Effect of Constraint Representation on Structural Tractability- Failure Analysis in Backtrack Search for Constraint Satisfaction- Heavy-Tailed Runtime Distributions: Heuristics, Models and Optimal Refutations- An Extension of Complexity Bounds and Dynamic Heuristics for Tree-Decompositions of CSP- Clique Inference Process for Solving Max-CSP- Global Grammar Constraints- Constraint Propagation for Domain Bounding in Distributed Task Scheduling- Interactive Distributed Configuration- Retroactive Ordering for Dynamic Backtracking

Principles and Practice of Constraint Programming - CP 2006 : 12th International Conference, CP 2006, Nantes, France, September 25-29, 2006 : proceedings

The introduction of the American ctenophore Mnemiopsis leidyi to the Black Sea was one of the most dramatic of all marine bioinvasions and, in combination with eutrophication and overfishing, resulted in a total reorganization of the pelagic food web and significant economic losses. Given the impacts this animal has exhibited in its invaded habitats, the spread of this ctenophore to additional regions has been a topic of much consternation. Here, we show the presence of this invader in estuaries along the Netherlands coast, based both on morphological observation and molecular evidence (nuclear internal transcribed spacer region 1 [ITS-1] sequence). Furthermore, we suggest the possibility that this ctenophore may have been present in Dutch waters for several years, having been misidentified as the morphologically similar Bolinopsis infundibulum. Given the level of shipping activity in nearby ports (e.g. Antwerp and Rotterdam), we find it likely that M. leidyi found its way to the Dutch coast in the ballast water of cargo ships, as is thought for Mnemiopsis in the Black and Caspian Seas. Given the magnitudes of the impacts this ctenophore has shown in its native and introduced ranges, the animal’s potential effects on the North Sea pelagic ecosystem and fisheries warrant close observation in the coming years. The development of large ctenophore aggregations during recent years was probably driven by the higher than average sea surface temperatures in the North Sea, and we hypothesize that populations from the southern North Sea may have been the source of the invaders reported in the Baltic Sea and the Skagerrak. If these northern populations (Baltic, etc.) are not able to over-winter, it is possible that established populations in southern North Sea estuaries may serve as a yearly supply of invaders to the colder waters to the north.

/pdf/the-ctenophore-mnemiopsis-leidyi-a-agassiz-1865-in-coastal-4nyeflrq93.pdf

The ctenophore Mnemiopsis leidyi A. Agassiz 1865 in coastal waters of the Netherlands: an unrecognized invasion?

Multi-Agent-Systems or MAS represent a powerful distributed computing model, enabling agents to cooperate and complete with each other and to exchange both semantic content and a semantic context to more automatically and accurately interpret the content. Many types of individual agent and MAS models have been proposed since the mid-1980s, but the majority of these have led to single developer homogeneous MAS systems. For over a decade, the FIPA standards activity has worked to produce public MAS specifications, acting as a key enabler to support interoperability, open service interaction, and to support heterogeneous development. The main characteristics of the FIPA model for MAS and an analysis of design, design choices and features of the model is presented. In addition, a comparison of the FIPA model for system interoperability versus those of other standards bodies is presented, along with a discussion of the current status of FIPA and future directions.

/pdf/specifying-protocols-for-multi-agent-systems-interaction-3834c5uyg7.pdf

Specifying protocols for multi-agent systems interaction

http://lifeware.inria.fr/~fages/Papers/GFMSS13dam.pdf

On the subgraph epimorphism problem

Despite the effort made to standardize agent communication languages, almost no tool has been developed to implement agents' conformance to their semantics. In this paper, we review the formal principles supporting the FIPA-ACL semantics and propose an operational model facilitating their implementation. This model has been implemented upon the JADE platform, resulting in more flexible agents, avoiding intensive use of rigid protocols.

An Operational Model for the FIPA-ACL Semantics

Petri nets are a simple formalism for modeling concurrent computation. They are also an interesting tool for modeling and analysing biochemical reaction systems, bridging the gap between purely qualitative and quantitative models. Biological networks can indeed be complex, large, and with many unknown kinetic parameters, which makes the development of quantitative models difficult. In this paper, we focus on the Petri net representation of biochemical reactions and on two structural properties of Petri nets, siphons and traps, that bring us information about the persistence of some molecular species, independently of the kinetics. We first study the theoretical time complexity of minimal siphon decision problems in general Petri nets, and present three new complexity results: first, we show that the existence of a siphon of a given cardinality is NP-complete; second, we prove that deciding the Siphon-Trap property is co-NP-complete; third, we prove that deciding the existence of a minimal siphon containing a given set of places, deciding the existence of a siphon of a given cardinality and deciding the Siphon-Trap property can be done in linear time in Petri nets of bounded tree-width. Then, we present a Boolean model of siphons and traps, and two method for enumerating all minimal siphons and traps of a Petri net, by using a SAT solver and a Constraint Logic Program (CLP) respectively. On a benchmark of 345 Petri nets of hundreds of places and transitions, extracted from biological models from the BioModels repository, as well as on a benchmark composed of 80 Petri nets from the Petriweb database of industrial processes, we show that both the SAT and CLP methods are overall faster by one or two orders of magnitude compared to the state-of-the-art algorithm from the Petri net community, and are in fact able to solve all the enumeration problems of our practical benchmarks. We investigate why these programs perform so well in practice, and provide some elements of explanation related to our theoretical complexity results.

/pdf/on-enumerating-minimal-siphons-in-petri-nets-using-clp-and-4d7d0rfk89.pdf

On enumerating minimal siphons in Petri nets using CLP and SAT solvers: theoretical and practical complexity

Bin packing is a classical combinatorial optimization problem which has a wide range of real-world applications in industry, logistics, transport, parallel computing, circuit design and other domains. While usually presented as discrete problems, we consider here continuous packing problems including curve shapes, and model these problems as continuous optimization problems with a multi-objective function combining non-overlapping with minimum bin size constraints. More specifically, we consider the covariance matrix adaptation evolution strategy (CMA-ES) with a non-overlapping and minimum size objective function in either two or three dimensions. Instead of taking the intersection area as measure of overlap, we propose other measures, monotonic with respect to the intersection area, to better guide the search. In order to compare this approach to previous work on bin packing, we first evaluate CMA-ES on Korf's benchmark of consecutive sizes square packing problems, for which optimal solutions are known, and on a benchmark of circle packing problems. We show that on square packing, CMA-ES computes solutions at typically 14% of the optimal cost, with the time limit given by the best dedicated algorithm for computing optimal solutions, and that on circle packing, the computed solutions are at 2% of the best known solutions. We then consider generalizations of this benchmark to mixed squares and circles, boxes, spheres and cylinders packing problems, and study a real-world problem for loading boxes and cylinders in containers. These hard problems illustrate the interesting trade-off between generality and efficiency in this approach.

On Solving Mixed Shapes Packing Problems by Continuous Optimization with the CMA Evolution Strategy

The Constraint Simplification Rules (CSR) subset of CHR and the flat subset of LCC, where agent nesting is restricted, are very close syntactically and semantically. The first contribution of this paper is to provide translations between CSR and flat-LCC. The second contribution is a transformation from the full LCC language to flat-LCC which preserves semantics. This transformation is similar to λ-lifting in functional languages. In conjunction with the equivalence between CHR and CSR with respect to the original operational semantics, these results lead to semantics-preserving translations from full LCC to CHR and conversely. Immediate consequences of this work include new proofs for CHR linear logic and phase semantics, relying on corresponding results for LCC, plus an encoding of the λ-calculus in CHR.

/pdf/semantics-preserving-translations-between-linear-concurrent-nny4q2fotc.pdf

Thierry Martinez

Papers

On the subgraph epimorphism problem

An Operational Model for the FIPA-ACL Semantics

On enumerating minimal siphons in Petri nets using CLP and SAT solvers: theoretical and practical complexity

On Solving Mixed Shapes Packing Problems by Continuous Optimization with the CMA Evolution Strategy

Semantics-preserving translations between linear concurrent constraint programming and constraint handling rules