Modelling of Multi-Agent Systems: Experiences with Membrane Computing and Future Challenges

Formal modelling of Multi-Agent Systems (MAS) is a challenging task due to high complexity, interaction, parallelism and continuous change of roles and organisation between agents. In this paper we record our research experience on formal modelling of MAS. We review our research throughout the last decade, by describing the problems we have encountered and the decisions we have made towards resolving them and providing solutions. Much of this work involved membrane computing and classes of P Systems, such as Tissue and Population P Systems, targeted to the modelling of MAS whose dynamic structure is a prominent characteristic. More particularly, social insects (such as colonies of ants, bees, etc.), biology inspired swarms and systems with emergent behaviour are indicative examples for which we developed formal MAS models. Here, we aim to review our work and disseminate our findings to fellow researchers who might face similar challenges and, furthermore, to discuss important issues for advancing research on the application of membrane computing in MAS modelling.Comment: In Proceedings AMCA-POP 2010, arXiv:1008.314

Predicting the outcomes of HIV treatment interruptions using computational modelling

In the past 30 years, HIV infection made a transition from fatal to chronic disease due to the emergence of potent treatment largely suppressing viral replication. However, this medication must be administered life-long on a regular basis to maintain viral suppression and is not always well tolerated. Any interruption of treatment causes residual virus to be reactivated and infection to progress, where the underlying processes occurring and consequences for the immune system are still poorly understood. Nonetheless, treatment interruptions are common due to adherence issues or limited access to antiretroviral drugs. Early clinical studies, aiming at application of treatment interruptions in a structured way, gave contradictory results concerning patient safety, discouraging further trials. In-silico models potentially add to knowledge but a review of the Literature indicates most current models used for studying treatment interruptions (equation-based), neglect recent clinical findings of collagen formation in lymphatic tissue due to HIV and its crucial role in immune system stability and efficacy. The aim of this research is the construction and application of so-called ‘Bottom-Up’ models to allow improved assessment of these processes in relation to HIV treatment interruptions. In this regard, a novel computational model based on 2D Cellular Automata for lymphatic tissue depletion and associated damage to the immune system was developed. Hence, (i) using this model, the influence of spatial distribution of collagen formation on HIV infection progression speed was evaluated while discussing aspects of computational performance. Further, (ii) direct Monte Carlo simulations were employed to explore the accumulation of tissue impairment due to repeated treatment interruptions and consequences for long-term prognosis. Finally, (iii) an inverse Monte Carlo approach was used to reconstruct yet unknown characteristics of patient groups. This is based on sparse data from past clinical studies on treatment interruptions with the aim of explaining their contradictory results

Estudio, Modelado e Implementación Paralela de Sistemas Celulares Utilizados en Microfabricación

La presente tesis toma como eje central el modelado de sistemas dinámicos mediante Autómatas Celulares (ACs). Los ACs permiten modelar un sistema enunciando el comportamiento microscópico a fin de obtener un comportamiento macroscópico correcto. Una de los principales campos donde esta metodología ha sido aplicada (y la cual forma otro de los puntos centrales de esta tesis) es el modelado del Grabado Anisótropo Húmedo (GAH). El GAH es un proceso químico el cual permite realizar microestructuras de silicio tridimensionales, lo que le ha permitido convertirse en una importante técnica de microfabricación. El GAH se utiliza para el micromaquinado de Sistemas Micro-Electro-Mecánicos (MEMS). Los MEMS consisten en la integración de elementos mecánicos, sensores, actuadores y electrónica en un substrato de silicio común a través de la tecnología de microfabricación. Los MEMS tienen una gran influencia en la industria puesto que dispositivos fabricados mediante esta tecnología se utilizan de forma intensiva en diversos campos tales como: sistemas de seguridad en automoción, sensores de movimiento en electrónica de consumo o inyectores en sistemas de impresión. El GAH es un proceso complejo cuyo resultado depende en gran medida de los diversos parámetros del proceso: (disolución, temperatura, tiempo), por lo que la utilización de un simulador previo a la realización del experimento puede suponer un gran ahorro en cuestión de tiempo y material. Los simuladores actuales de GAH basados en ACs poseen diversas limitaciones: Tiempos de computación muy elevados debido a los altos requisitos computacionales de los ACs, un reducido conjunto de calibraciones existentes, así como la imposibilidad de simular el GAH basado en nuevos atacantes tales como TMAH+Triton. La resolución de estas limitaciones es abordada en diversos capítulos de la tesis.Ferrando Jódar, N. (2011). Estudio, Modelado e Implementación Paralela de Sistemas Celulares Utilizados en Microfabricación [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10984Palanci