We compare the hybrid, stochastic, and differential semantics for stochastic Concurrent Constraint Programming, focussing on the exhibited behavior of models and their robustness. By investigating in detail two case studies, a circadian clock model and the Repressilator, we comment on the effect of the introduction of a limited amount of discreteness in the description of biological systems with hybrid automata. Experimental evidence suggests that discreteness increases robustness of the models
AbstractWe present a stochastic version of Concurrent Constraint Programming (CCP), where we associa...
International audienceWe address the inclusion of stochastic information into an explicitly timed co...
We present a technique to approximate models of biological systems written in a "distilled" version ...
AbstractWe compare the hybrid, stochastic, and differential semantics for stochastic Concurrent Cons...
We compare the hybrid, stochastic, and differential semantics for stochastic Concurrent Constraint P...
AbstractWe provide Stochastic Concurrent Constraint Programming (sCCP), a stochastic process algebra...
We provide Stochastic Concurrent Constraint Programming (sCCP), a stochastic process algebra based o...
We provide Stochastic Concurrent Constraint Programming (sCCP), a stochastic process algebra based o...
We define a semantics for stochastic Concurrent Constraint Programming (sCCP), a stochastic process ...
We address the inclusion of stochastic information into an explicitly timed concurrent constraint pr...
We define a semantics for stochastic Concurrent Constraint Programming (sCCP), a stochastic process ...
We present a technique to associate to stochastic programs written in stochastic Concurrent Constrai...
We investigate the behaviour of population models written in Stochastic Concurrent Constraint Progra...
Building on a technique for associating Hybrid Systems (HS) to stochastic programs written in a stoc...
We investigate the behaviour of population models, specified in stochastic Concurrent Constraint Pro...
AbstractWe present a stochastic version of Concurrent Constraint Programming (CCP), where we associa...
International audienceWe address the inclusion of stochastic information into an explicitly timed co...
We present a technique to approximate models of biological systems written in a "distilled" version ...
AbstractWe compare the hybrid, stochastic, and differential semantics for stochastic Concurrent Cons...
We compare the hybrid, stochastic, and differential semantics for stochastic Concurrent Constraint P...
AbstractWe provide Stochastic Concurrent Constraint Programming (sCCP), a stochastic process algebra...
We provide Stochastic Concurrent Constraint Programming (sCCP), a stochastic process algebra based o...
We provide Stochastic Concurrent Constraint Programming (sCCP), a stochastic process algebra based o...
We define a semantics for stochastic Concurrent Constraint Programming (sCCP), a stochastic process ...
We address the inclusion of stochastic information into an explicitly timed concurrent constraint pr...
We define a semantics for stochastic Concurrent Constraint Programming (sCCP), a stochastic process ...
We present a technique to associate to stochastic programs written in stochastic Concurrent Constrai...
We investigate the behaviour of population models written in Stochastic Concurrent Constraint Progra...
Building on a technique for associating Hybrid Systems (HS) to stochastic programs written in a stoc...
We investigate the behaviour of population models, specified in stochastic Concurrent Constraint Pro...
AbstractWe present a stochastic version of Concurrent Constraint Programming (CCP), where we associa...
International audienceWe address the inclusion of stochastic information into an explicitly timed co...
We present a technique to approximate models of biological systems written in a "distilled" version ...