CASP Solutions for Planning in Hybrid Domains

CASP is an extension of ASP that allows for numerical constraints to be added in the rules. PDDL+ is an extension of the PDDL standard language of automated planning for modeling mixed discrete-continuous dynamics. In this paper, we present CASP solutions for dealing with PDDL+ problems, i.e., encoding from PDDL+ to CASP, and extensions to the algorithm of the EZCSP CASP solver in order to solve CASP programs arising from PDDL+ domains. An experimental analysis, performed on well-known linear and non-linear variants of PDDL+ domains, involving various configurations of the EZCSP solver, other CASP solvers, and PDDL+ planners, shows the viability of our solution.Comment: Under consideration in Theory and Practice of Logic Programming (TPLP

A Method to Identify and Analyze Biological Programs through Automated Reasoning.

Predictive biology is elusive because rigorous, data-constrained, mechanistic models of complex biological systems are difficult to derive and validate. Current approaches tend to construct and examine static interaction network models, which are descriptively rich but often lack explanatory and predictive power, or dynamic models that can be simulated to reproduce known behavior. However, in such approaches implicit assumptions are introduced as typically only one mechanism is considered, and exhaustively investigating all scenarios is impractical using simulation. To address these limitations, we present a methodology based on automated formal reasoning, which permits the synthesis and analysis of the complete set of logical models consistent with experimental observations. We test hypotheses against all candidate models, and remove the need for simulation by characterizing and simultaneously analyzing all mechanistic explanations of observed behavior. Our methodology transforms knowledge of complex biological processes from sets of possible interactions and experimental observations to precise, predictive biological programs governing cell function

Solving Set Constraint Satisfaction Problems using ROBDDs

In this paper we present a new approach to modeling finite set domain constraint problems using Reduced Ordered Binary Decision Diagrams (ROBDDs). We show that it is possible to construct an efficient set domain propagator which compactly represents many set domains and set constraints using ROBDDs. We demonstrate that the ROBDD-based approach provides unprecedented flexibility in modeling constraint satisfaction problems, leading to performance improvements. We also show that the ROBDD-based modeling approach can be extended to the modeling of integer and multiset constraint problems in a straightforward manner. Since domain propagation is not always practical, we also show how to incorporate less strict consistency notions into the ROBDD framework, such as set bounds, cardinality bounds and lexicographic bounds consistency. Finally, we present experimental results that demonstrate the ROBDD-based solver performs better than various more conventional constraint solvers on several standard set constraint problems

Generic Traces and Constraints, GenTra4CP revisited

The generic trace format GenTra4CP has been defined in 2004 with the goal of becoming a standard trace format for the observation of constraint solvers over finite domains. It has not been used since. This paper defines the concept of generic trace formally, based on simple transformations of traces. It then analyzes, and occasionally corrects, shortcomings of the proposed initial format and shows the interest that a generic tracer may bring to develop portable applications or to standardization efforts, in particular in the field of constraints

solveME: fast and reliable solution of nonlinear ME models.

BackgroundGenome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challenges: they are much (>30 times) larger than corresponding metabolic reconstructions (M models), are multiscale, and growth maximization is a nonlinear programming (NLP) problem, mainly due to macromolecule dilution constraints.ResultsHere, we address these computational challenges. We develop a fast and numerically reliable solution method for growth maximization in ME models using a quad-precision NLP solver (Quad MINOS). Our method was up to 45 % faster than binary search for six significant digits in growth rate. We also develop a fast, quad-precision flux variability analysis that is accelerated (up to 60× speedup) via solver warm-starts. Finally, we employ the tools developed to investigate growth-coupled succinate overproduction, accounting for proteome constraints.ConclusionsJust as genome-scale metabolic reconstructions have become an invaluable tool for computational and systems biologists, we anticipate that these fast and numerically reliable ME solution methods will accelerate the wide-spread adoption of ME models for researchers in these fields

Applying constraint solving to the management of distributed applications

Submitted to DOA08We present our approach for deploying and managing distributed component-based applications. A Desired State Description (DSD), written in a high-level declarative language, specifies requirements for a distributed application. Our infrastructure accepts a DSD as input, and from it automatically configures and deploys the distributed application. Subsequent violations of the original requirements are detected and, where possible, automatically rectified by reconfiguration and redeployment of the necessary application components. A constraint solving tool is used to plan deployments that meet the application requirements.Postprin

Checking Computations of Formal Method Tools - A Secondary Toolchain for ProB

We present the implementation of pyB, a predicate - and expression - checker for the B language. The tool is to be used for a secondary tool chain for data validation and data generation, with ProB being used in the primary tool chain. Indeed, pyB is an independent cleanroom-implementation which is used to double-check solutions generated by ProB, an animator and model-checker for B specifications. One of the major goals is to use ProB together with pyB to generate reliable outputs for high-integrity safety critical applications. Although pyB is still work in progress, the ProB/pyB toolchain has already been successfully tested on various industrial B machines and data validation tasks.Comment: In Proceedings F-IDE 2014, arXiv:1404.578

Constraint Logic Programming for Natural Language Processing

This paper proposes an evaluation of the adequacy of the constraint logic programming paradigm for natural language processing. Theoretical aspects of this question have been discussed in several works. We adopt here a pragmatic point of view and our argumentation relies on concrete solutions. Using actual contraints (in the CLP sense) is neither easy nor direct. However, CLP can improve parsing techniques in several aspects such as concision, control, efficiency or direct representation of linguistic formalism. This discussion is illustrated by several examples and the presentation of an HPSG parser.Comment: 15 pages, uuencoded and compressed postscript to appear in Proceedings of the 5th Int. Workshop on Natural Language Understanding and Logic Programming. Lisbon, Portugal. 199