20 papers · ranked by Valyu relevance
Suyog Chandramouli, Danqing Shi, Aini Putkonen, Sebastiaan De Peuter + 4 more
Computational rationality explains human behavior as arising due to the maximization of expected utility under the constraints imposed by the environment and limited cognitive resources. This simple assumption, when instantiated via partially observable Markov decision processes (POMDPs), gives rise to a powerful…
Ovidiu Pârvu, David Gilbert
Background Computational models play an increasingly important role in systems biology for generating predictions and in synthetic biology as executable prototypes/designs. For real life (clinical) applications there is a need to scale up and build more complex spatio-temporal multiscale models; these could enable…
Miguel Carrillo, Pedro A. Góngora, David A. Rosenblueth
Model checking is a well-established technique for automatically verifying complex systems. Recently, model checkers have appeared in computer tools for the analysis of biochemical (and gene regulatory) networks. We survey several such tools to assess the potential of model checking in computational biology. Next, our…
Savas Konur, Marian Gheorghe, Natalio Krasnogor
The formalization of biological systems using computational modelling approaches as an alternative to mathematical-based methods has recently received much interest because computational models provide a deeper mechanistic understanding of biological systems. In particular, formal verification, complementary approach…
Wassim Abou-Jaoudé, Pedro T. Monteiro, Aurélien Naldi, Maximilien Grandclaudon + 3 more
Computational modeling constitutes a crucial step towards the functional understanding of complex cellular networks. In particular, logical modeling has proven suitable for the dynamical analysis of large signaling and transcriptional regulatory networks. In this context, signaling input components are generally meant…
Alberto Molinari
Model checking (MC) is a family of formal methods that have been accepted by industry and are becoming integral part of standards and of system development cycles. In MC, some properties of a finite-state transition system are expressed in suitable specification languages and then verified over a model of the system…
Hadrien Bride, Cheng‐Hao Cai, Jin Song Dong, Rajeev Goré + 3 more
'Brendan Mahony' 'J. Michael McCarthy'] Abstract. N-PAT is a new model-checking tool that supports the verification of nested-models, i.e. models whose behaviour depends on the results of verification tasks. In this paper, we describe its operation and discuss mechanisms that are tailored to the efficient verification…
Colin Thomas, Maximilien Cosme, Cédric Gaucherel, Franck Pommereau
Model-checking is a methodology developed in computer science to automatically assess the dynamics of discrete systems, by checking if a system modelled as a state-transition graph satisfies a dynamical property written as a temporal logic formula. The dynamics of ecosystems have been drawn as state-transition graphs…
Arlen Cox, Jason Leasure
Even the fastest SMT solvers have performance problems with regular expressions from real programs. Because these performance issues often arise from the problem representation (e.g. non-deterministic finite automata get determinized and regular expressions get unrolled), we revisit Boolean finite automata, which allow…
Ovidiu Pârvu, David Gilbert, Attila Csikász-Nagy
Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking…
Shahbaz Ali, Hailong Sun, Yongwang Zhao
The quality and correct functioning of software components embedded in electronic systems are of utmost concern especially for safety and mission-critical systems. Model-based testing and formal verification techniques can be employed to enhance the reliability of software systems. Formal models form the basis and are…
Igor Buzhinsky, Valeriy Vyatkin
Model checking is an established technique to formally verify automation systems which are required to be trusted. However, for sufficiently complex systems model checking becomes computationally infeasible. On the other hand, testing, which offers less reliability, often does not present a serious computational…
Céline Hernandez, Morgane Thomas-Chollier, Aurélien Naldi, Denis Thieffry
At the crossroad between biology and mathematical modelling, computational systems biology can contribute to a mechanistic understanding of high-level biological phenomenon. But as our knowledge accumulates, the size and complexity of mathematical models increase, calling for the development of efficient dynamical…
Katharina Götz, Patric Feldmeier, Gordon Fraser
—Learners are often introduced to programming via dedicated languages such as SCRATCH, where block-based commands are assembled visually in order to control the interactions of graphical sprites. Automated testing of such programs is an important prerequisite for supporting debugging, providing hints, or assessing…
Woosub Shin, Joseph L. Hellerstein
The growing complexity of reaction-based models necessitates early detection and resolution of model errors. This paper addresses mass balance errors, discrepancies between the mass of reactants and products in reaction specifications. One approach to detection is atomic mass analysis, which uses meta-data to expose…
Edward A. Lee, Albert M. K. Cheng
This paper is about better engineering of cyber-physical systems (CPSs) through better models. Deterministic models have historically proven extremely useful and arguably form the kingpin of the industrial revolution and the digital and information technology revolutions. Key deterministic models that have proven…
Sabah Al‐Fedaghi
—A conceptual model is used to support development and design within the area of systems and software modeling. The notion of validation refers to representing a domain in a model accurately and generating results using an executable model. In UML specifications, validation verifies the correctness of UML diagrams…
Authors not listed
Deriving versatile and robust mechanistic models from experimental data is a key challenge in engineering and natural sciences. This is especially true in chemical reaction engineering, where reactor manufacturers and operators increasingly pursue the development and maintenance of digital twins that rely on frequent…
Authors not listed
Step-by-step thinking is essential in all domains of chemical sciences and engineering. While machine learning tools are broadly used, algorithms that automate reasoning are far less common. We elaborate on seven categories of human reasoning activities and connect each to applications in chemical science and…
Tianfan Jin, Brett M Savoie
Contemporary machine learning algorithms have largely succeeded in automating the development of mathematical models from data. Although this is a striking accomplishment, it leaves unaddressed the multitude of scenarios, especially across the chemical sciences and engineering, where deductive, rather than inductive…