Structured Argumentation for Simulation-Based Research

Scientific research is a vanguard domain of human activity. Researchers aim for a systematic, objective approach, but also for pushing forward the boundaries of knowledge through the use of ever-more advanced instruments and techniques. Computer simulations represent such scientific instruments, capable of harvesting information in response to questions beyond the scope of traditional experimental techniques. The benefits of using them must, however, be considered together with aspects that led to criticism and lack of confidence e.g. they are difficult to analyze and validate, assumptions are only partially managed. This thesis scopes down the vast domain of simulation-based research, to the use of agent-based simulations for studying complex systems. The use of structured argumentation in a scientific research context is studied as a means for addressing the core limitations of simulation-based research. The Goal Structuring Notation has been used effectively in its originating domain - Safety Critical Systems - in addressing similar problems to simulation-based research. Through the use of this notation, this research emphasizes the difficulty of expressing compelling arguments, even in journal publications; in addition, it propose a set of extensions to the notation in order to adapt it to the scientific discourse. Finally, it shows the implications of studying a model in a rigorous, exhaustive manner, over the claims that can be made through it

Systems analysis of auxin transport in the Arabidopsis root apex

Auxin is a key regulator of plant growth and development. Within the root tip, auxin distribution plays a crucial role specifying developmental zones and coordinating tropic responses. Determining how the organ-scale auxin pattern is regulated at the cellular scale is essential to understanding how these processes are controlled. In this study, we developed an auxin transport model based on actual root cell geometries and carrier subcellular localizations. We tested model predictions using the DII-VENUS auxin sensor in conjunction with state-of-the-art segmentation tools. Our study revealed that auxin efflux carriers alone cannot create the pattern of auxin distribution at the root tip and that AUX1/LAX influx carriers are also required. We observed that AUX1 in lateral root cap (LRC) and elongating epidermal cells greatly enhance auxin’s shootward flux, with this flux being predominantly through the LRC, entering the epidermal cells only as they enter the elongation zone. We conclude that the nonpolar AUX1/LAX influx carriers control which tissues have high auxin levels, whereas the polar PIN carriers control the direction of auxin transport within these tissues

Emergence of Frontiers in networked Schelling segregationist models

International audienceThe relation between individuality and aggregation is an important topic in complex systems sciences, both aspects being facets of emergence. This topic has frequently been addressed by adopting a classical, individual versus population level perspective. Here, however, the frontiers that emerge in segregated communities are the focus; segregation is synonymous with the existence of frontiers that delineate and interface aggregates. A generic agent-based model is defined, with which we simulate communities located on grid and scale-free networked environments. Emerging frontiers are analyzed in terms of their relative occupancy, porosity, and permeability. Results emphasize that the frontier is highly sensitive to the topology of the environment, not only to the agent tolerance. These relations are clarified while addressing the topics of frontier robustness and the trade-off between its capacity to separate and allow exchange

Reflections on the Simulation of Complex Systems for Science

In studying complex systems, agent-based simulations offer the possibility of directly modelling components in an environment. However, the scientific value of agent-based simulations has been limited by inadequate scientific rigour. The paper focuses on agent-based simulations that are used in biological and bio-medical research. Starting from a review of best practice in simulation engineering, the paper identifies some of the key activities in developing complex systems simulations that support scientific research, and how these contribute to the essential development of mutual trust among developers and scientists. Examples from the authors' own experience illustrate how a range of studies have manifested these key activities, and identifies some successes and problems encountered