Dissertation: Narrative Generation for Agent-Based Models

Abstract: This dissertation proposes a four-level framework for thinking about having agent-based models (ABM) generate narrative describing their behavior, and then provides examples of models that generate narrative at each of those levels. In addition, “interesting” agents are identified in order to direct the attention of researchers to the narratives most likely to be worth spending their time reviewing. The focus is on developing techniques for generating narrative based on agent actions and behavior, on techniques for generating narrative describing aggregate model behavior, and on techniques for identifying “interesting” agents. Examples of each of these techniques are provided in two different ABMs, Zero-Intelligence Traders (Gode & Sunder, 1993, 1997) and Sugarscape (Epstein & Axtell, 1996).

Ecology - Natural Resources Management (Community-based management)

I worked on natural resources management modelling in STELLA. I developed a technical and scientific model to analyze soil, climate and biological conditions to explain how Bamboo ecosystem works and how people in Cundinamarca, Colombia could focus on a sustainable model for use and manage forestry resources.
Also, I worked on the seventh framework program named: Community-based management of Environmental Challenges in Latin America -COMET-LA-. The project built a learning arena with scientists, civil society and government to identify sustainable models for governance of natural resources in social-ecological systems located in a rural context from Colombia, México and Argentina.

I am interesting in research on Modelling of governance and Community-based management of natural resources.

Agent based modelling and simulation.
Mental heath and wellbeing.

Interested in numerical models and new conceptual ideas, applications from industry to medicine.

I focus on numerical modeling of mechanics of solid materials and cell mechanics. The models that I developed so far address granular matters, bio-fluids, cellular tissues, and individual cells.

I further develop Agent-based Models, which are methods to predict collective behavior from individual dynamics controlled by rules or differential equations. Examples: tumor growth, swarms, crowd movement.

The methods I used are Particle-based methods which offer great flexibility within physical modeling, and can operate in a large range of scales, from atomistic scales (e.g. Molecular Dynamics) to continuum approaches (e.g. Smoothed Particle Hydrodynamics).

I’m interested in inter-individual interactions in general, demo-genetics and group behaviour. I’m currently working on locusts. Visit my website for more info.

My PHD project focuses on understanding factors influencing individual sustainable consumption behaviour and how these factors could promote a sustainability transition.

Behavioural ecology and modelling of ant behaviour, with an emphasis on understanding how individual-level complexity affects collective decision-making

Currently working on Agent Based Demography.

I am investigating the use of machine learning techniques in non-stationary modeling environments to better reproduce aspects of human learning and decision-making in human-natural system simulations.

-Use of models, including agent-based models, in understanding the formation of surface archaeological deposits in arid Australia
-Individual-based modelling of resource use on marginal islands in Polynesian prehistory
-Individual-based modelling of the influence of serial voyaging events on body proportions in Remote Oceania
-Discrete event simulation of early horticultural production in New Zealand