73 search results - page 2 / 15 » Deterministic and stochastic P systems for modelling cellula... |
GECCO
2008
Springer
13 years 6 months ago
2008
Springer
In this work we present a new methodology for structure and parameter estimation in cell systems biology modelling. Our modelling framework is based on P systems, an unconl comput...
CSB
2003
IEEE
13 years 10 months ago
2003
IEEE
We have constructed a computer model of the cytotoxic T lymphocyte (CTL) response to antigen and the maintenance of immunological memory. Because immune responses often begin with...
JAIR
2011
12 years 12 months ago
2011
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
WSC
1998
13 years 6 months ago
1998
Bayesian forecasting models provide distributional estimates for random parameters, and relative to classical schemes, have the advantage that they can rapidly capture changes in ...
ANTSW
2010
Springer
12 years 12 months ago
2010
Springer
Abstract. Ant algorithms are usually derived from a stochastic modeling based on some specific probability laws. We consider in this paper a full deterministic model of "logis...