Arnaud Grignard

GAMA 1.6: Advancing the Art of Complex Agent-Based Modeling and Simulation

Agent-based models tend to be more and more complex. In order to cope with this increase of complexity, powerful modeling and simulation tools are required. These last years have seen the development of several platforms dedicated to the development of agent-based models. While some of them are still limited to the development of simple models, others allow to develop rich and complex models. Among them, the GAMA modeling and simulation platform is aimed at supporting the design of spatialized, multiple-paradigms and multiple-scales models. Several papers have already introduced GAMA, notably in earlier PRIMA conferences, and we would like, in this paper, to introduce the new features provided by GAMA 1.6, the latest revision to date of the platform. In particular, we present its capabilities concerning the tight combination of 3D visualization, GIS data management, and multi-level modeling. In addition, we present some examples of real projects that rely on GAMA to develop complex models.

A Simple-to-Use BDI Architecture for Agent-Based Modeling and Simulation

With the increase of computing power and the development of user-friendly multi-agent simulation frameworks, social simulations have become increasingly realistic. However, most agent architectures in these simulations use simple reactive models. Cognitive architectures face two main obstacles: their complexity for the field-expert modeler, and their computational cost. In this paper, we propose a new cognitive agent architecture based on the Belief-Desire-Intention paradigm integrated into the GAMA modeling platform. Based on the GAML modeling language, this architecture was designed to be simple-to-use for modelers, flexible enough to manage complex behaviors, and with low computational cost. This architecture is illustrated with a simulation of the evolution of land-use in the Mekong Delta.

GAMA: A Spatially Explicit, Multi-level, Agent-Based Modeling and Simulation Platform

Agent-based modeling is now widely used to investigate complex systems but still lacks integrated and generic tools to support the representation of features usually associated with real complex systems, namely rich, dynamic and realistic environments or multiple levels of agency. The GAMA platform has been developed to address such issues and allow modelers, thanks to the use of a high-level modeling language, to build, couple and reuse complex models combining various agent architectures, environment representations and levels of abstraction.

Reproducing and exploring past events using agent-based geo-historical models

The field of “digital humanities” is about using the latest digital methodologies in order to tackle humanities disciplines and social sciences questions. The ARCHIVES project belongs to this new research area. It proposes a methodology to build agent-based models of historical events, in particular crisis events, in order to answer new questions about them or explore them in new ways. In this paper, we present the first implementation of ARCHIVES on the case study of the management of floods in Ha Nội (Việt Nam) in 1926. We show how we collected, digitized and indexed numerous historical documents from various sources, built a historical geographic information system to represent the environment and flooding events and finally designed an agent-based model of human activities in this reconstructed environment. We then show how this model helped us understanding the decisions made by the different actors during this event, testing multiple scenarios and answering several questions concerning the management of the flooding events.

CityScope: A Data-Driven Interactive Simulation Tool for Urban Design. Use Case Volpe

MIT City Science Group (CS) studies the interaction of social, economic and physical characteristics of urban areas to understand how people use and experience cities with the goal of improving urban design practices to facilitate consensus between stakeholders. Long-established processes of engagement around urban transformation have been reliant on visual communication and complex negotiation to facilitate coordination between stakeholders, including community members, administrative bodies and technical professionals. City Science group proposes a novel methodology of interaction and collaboration called CityScope, a data-driven platform that simulates the impacts of interventions on urban ecosystems prior to detail-design and execution. As stakeholders collectively interact with the platform and understand the impact of proposed interventions in real-time, consensus building and optimization of goals can be achieved. In this article, we outline the methodology behind the basic analysis and visualization elements of the tool and the tangible user interface, to demonstrate an alternate solution to urban design strategies as applied to the Volpe Site case study in Kendall Square, Cambridge, MA.

Agent-Based Visualization: A Simulation Tool for the Analysis of River Morphosedimentary Adjustments

Spatially explicit agent-based models and simulations are playing an increasing role in the modelling of complex natural and social systems. The ARCHEM project belongs to this new research area. It proposes a new methodology to visualize the fine-scale sediment transport of a river. In this paper, we present the first implementation of ARCHEM on a case study of the Rhone river. Even though visualization cannot replace the analysis of simulation results, it often constitutes a more accessible medium that can facilitate more specific and accurate interpretations of simulation output. It has the advantage of offering immediate feedback as well as a way to interact with and analyze results. We show how to support multiple viewpoints and different levels of abstraction using an agent-based visualization approach. We present a specific application focusing on dynamical 3D rendering of a GIS file and the analysis of morphosedimentary adjustments.

Complex systems simulation online visual analysis and assessment using dynamic aggregation operators

Agent-Based Simulations generate massive loads of data that need to be analyzed and visualized online. This paper proposes an approach that represents and abstracts dynamical properties of agent-based model using visual abstract operator. We present how spatio-temporal dynamic aggregation operators can facilitate online analysis tool of agent-based simulation. Spatial aggregation is used to represent multi level model with hierarchical and density-based clustering. Temporal aggregation is used for agent trajectory analysis and dynamic network analysis. Such an approach is related to data stream mining which is the process of extracting knowledge structures from continuous data records. It goes beyond visualization as the information displayed is the result of mining algorithms that are performed on the stream of data from the ABM simulation.

The Impact of New Mobility Modes on a City: A Generic Approach Using ABM

Mobility is a key issue for city planners. Being able to evaluate the impact of its evolution is complex and involves many factors including new technologies like electric cars, autonomous vehicles and also new social habits like vehicle sharing. We need a better understanding of different scenarios to improve the quality of long-term decisions. Computer simulations can be a tool to better understand this evolution, to discuss different solutions and to communicate the implications of different decisions. In this paper, we propose a new generic model that creates an artificial micro-world which allows the modeler to create and modify new mobility scenarios in a quick and easy way. This not only helps to better understand the impact of new mobility modes on a city, but also fosters a better-informed discussion of different futures. Our model is based on the agent-based paradigm using the GAMA Platform. It takes into account different mobility modes, people profiles, congestion and traffic patterns. In this paper, we review an application of the model of the city of Cambridge.