RESUMEN
Simulation is a key tool for researching complex system behaviour. Agent-based simulation has been applied across domains, such as biology, health, economics and urban sciences. However, engineering robust, efficient, maintainable, and reliable agent-based simulations is challenging. We present a vision for engineering agent simulations comprising a family of domain-specific modelling languages (DSMLs) that integrates core software engineering, validation and simulation experimentation. We relate the vision to examples of principled simulation, to show how the DSMLs would improve robustness, efficiency, and maintainability of simulations. Focusing on how to demonstrate the fitness for purpose of a simulator, the envisaged approach supports bi-directional transparency and traceability between the original domain understanding to the implementation, interpretation of results and evaluation of hypotheses.
RESUMEN
Simulations of evolutionary dynamics often employ white noise as a model of stochastic environmental variation. Whilst white noise has the advantages of being simply generated and analytically tractable, empirical analyses demonstrate that most real environmental time series have power spectral densities consistent with pink or red noise, in which lower frequencies contribute proportionally greater amplitudes than higher frequencies. Simulated white noise environments may therefore fail to capture key components of real environmental time series, leading to erroneous results. To explore the effects of different noise colours on evolving populations, a simple evolutionary model of the interaction between life-history and the specialism-generalism axis was developed. Simulations were conducted using a range of noise colours as the environments to which agents adapted. Results demonstrate complex interactions between noise colour, reproductive rate, and the degree of evolved generalism; importantly, contradictory conclusions arise from simulations using white as opposed to red noise, suggesting that noise colour plays a fundamental role in generating adaptive responses. These results are discussed in the context of previous research on evolutionary responses to fluctuating environments, and it is suggested that Artificial Life as a field should embrace a wider spectrum of coloured noise models to ensure that results are truly representative of environmental and evolutionary dynamics.
RESUMEN
In May 2019, a workshop on principled development of future agent-based simulations was held at Keele University. Participants spanned companies and academia, and a range of domains of interest, as well as participant career stages. This report summarizes the discussions and main outcomes from this workshop.
Asunto(s)
Biología Computacional , Simulación por Computador , Vida , Congresos como Asunto , Inglaterra , HumanosRESUMEN
The application of computational and mathematical modelling to explore the mechanics of biological systems is becoming prevalent. To significantly impact biological research, notably in developing novel therapeutics, it is critical that the model adequately represents the captured system. Confidence in adopting in silico approaches can be improved by applying a structured argumentation approach, alongside model development and results analysis. We propose an approach based on argumentation from safety-critical systems engineering, where a system is subjected to a stringent analysis of compliance against identified criteria. We show its use in examining the biological information upon which a model is based, identifying model strengths, highlighting areas requiring additional biological experimentation and providing documentation to support model publication. We demonstrate our use of structured argumentation in the development of a model of lymphoid tissue formation, specifically Peyer's Patches. The argumentation structure is captured using Artoo (www.york.ac.uk/ycil/software/artoo), our Web-based tool for constructing fitness-for-purpose arguments, using a notation based on the safety-critical goal structuring notation. We show how argumentation helps in making the design and structured analysis of a model transparent, capturing the reasoning behind the inclusion or exclusion of each biological feature and recording assumptions, as well as pointing to evidence supporting model-derived conclusions.
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Tejido Linfoide/patología , Ganglios Linfáticos Agregados/fisiología , Algoritmos , Animales , Movimiento Celular , Simulación por Computador , Humanos , Internet , Modelos Biológicos , Programas InformáticosRESUMEN
Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions.
Asunto(s)
Simulación por Computador , Modelos Biológicos , Neoplasias/metabolismo , Transducción de Señal , Biología de Sistemas , Animales , Antineoplásicos/química , Antineoplásicos/farmacología , Gráficos por Computador , Diseño Asistido por Computadora , Diseño de Fármacos , Humanos , Terapia Molecular Dirigida , Neoplasias/tratamiento farmacológico , Neoplasias/genética , Neoplasias/patología , Reproducibilidad de los Resultados , Transducción de Señal/efectos de los fármacos , Transducción de Señal/genética , Diseño de SoftwareRESUMEN
Quantum error-correcting codes can protect multipartite quantum states from errors on some limited number of their subsystems (usually qubits). We construct a family of Bell inequalities which inherit this property from the underlying code and exhibit the violation of local realism, without any quantum information processing (except for the creation of an entangled state). This family shows no reduction in the size of the violation of local realism for arbitrary errors on a limited number of qubits. Our minimal construction requires preparing an 11-qubit entangled state.