1,789 research outputs found
CONJURE: automatic generation of constraint models from problem specifications
Funding: Engineering and Physical Sciences Research Council (EP/V027182/1, EP/P015638/1), Royal Society (URF/R/180015).When solving a combinatorial problem, the formulation or model of the problem is critical tothe efficiency of the solver. Automating the modelling process has long been of interest because of the expertise and time required to produce an effective model of a given problem. We describe a method to automatically produce constraint models from a problem specification written in the abstract constraint specification language Essence. Our approach is to incrementally refine the specification into a concrete model by applying a chosen refinement rule at each step. Any nontrivial specification may be refined in multiple ways, creating a space of models to choose from. The handling of symmetries is a particularly important aspect of automated modelling. Many combinatorial optimisation problems contain symmetry, which can lead to redundant search. If a partial assignment is shown to be invalid, we are wasting time if we ever consider a symmetric equivalent of it. A particularly important class of symmetries are those introduced by the constraint modelling process: modelling symmetries. We show how modelling symmetries may be broken automatically as they enter a model during refinement, obviating the need for an expensive symmetry detection step following model formulation. Our approach is implemented in a system called Conjure. We compare the models producedby Conjure to constraint models from the literature that are known to be effective. Our empirical results confirm that Conjure can reproduce successfully the kernels of the constraint models of 42 benchmark problems found in the literature.Publisher PDFPeer reviewe
When rule-based models need to count
Rule-based modelers dislike direct enumeration of cases when more efficient
means of enumeration are available. We present an extension of the Kappa
language which attaches to agents a notion of level. We detail two encodings
that are more concise than the former practice
Rule-based Modelling and Tunable Resolution
We investigate the use of an extension of rule-based modelling for cellular
signalling to create a structured space of model variants. This enables the
incremental development of rule sets that start from simple mechanisms and
which, by a gradual increase in agent and rule resolution, evolve into more
detailed descriptions
An Intuitive Automated Modelling Interface for Systems Biology
We introduce a natural language interface for building stochastic pi calculus
models of biological systems. In this language, complex constructs describing
biochemical events are built from basic primitives of association, dissociation
and transformation. This language thus allows us to model biochemical systems
modularly by describing their dynamics in a narrative-style language, while
making amendments, refinements and extensions on the models easy. We
demonstrate the language on a model of Fc-gamma receptor phosphorylation during
phagocytosis. We provide a tool implementation of the translation into a
stochastic pi calculus language, Microsoft Research's SPiM
Exploiting Symmetries When Proving Equivalence Properties for Security Protocols
International audienceVerification of privacy-type properties for cryptographic protocols in an active adversarial environment, modelled as a behavioural equivalence in concurrent-process calculi, exhibits a high computational complexity. While undecidable in general, for some classes of common cryptographic primitives the problem is coNEXP-complete when the number of honest participants is bounded.In this paper we develop optimisation techniques for verifying equivalences, exploiting symmetries between the two processes under study. We demonstrate that they provide a significant (several orders of magnitude) speed-up in practice, thus increasing the size of the protocols that can be analysed fully automatically
Thermodynamic graph-rewriting
We develop a new thermodynamic approach to stochastic graph-rewriting. The
ingredients are a finite set of reversible graph-rewriting rules called
generating rules, a finite set of connected graphs P called energy patterns and
an energy cost function. The idea is that the generators define the qualitative
dynamics, by showing which transformations are possible, while the energy
patterns and cost function specify the long-term probability of any
reachable graph. Given the generators and energy patterns, we construct a
finite set of rules which (i) has the same qualitative transition system as the
generators; and (ii) when equipped with suitable rates, defines a
continuous-time Markov chain of which is the unique fixed point. The
construction relies on the use of site graphs and a technique of `growth
policy' for quantitative rule refinement which is of independent interest. This
division of labour between the qualitative and long-term quantitative aspects
of the dynamics leads to intuitive and concise descriptions for realistic
models (see the examples in S4 and S5). It also guarantees thermodynamical
consistency (AKA detailed balance), otherwise known to be undecidable, which is
important for some applications. Finally, it leads to parsimonious
parameterizations of models, again an important point in some applications
Discovering Knowledge using a Constraint-based Language
Discovering pattern sets or global patterns is an attractive issue from the
pattern mining community in order to provide useful information. By combining
local patterns satisfying a joint meaning, this approach produces patterns of
higher level and thus more useful for the data analyst than the usual local
patterns, while reducing the number of patterns. In parallel, recent works
investigating relationships between data mining and constraint programming (CP)
show that the CP paradigm is a nice framework to model and mine such patterns
in a declarative and generic way. We present a constraint-based language which
enables us to define queries addressing patterns sets and global patterns. The
usefulness of such a declarative approach is highlighted by several examples
coming from the clustering based on associations. This language has been
implemented in the CP framework.Comment: 12 page
- …