David Masad’s research while affiliated with George Mason University and other places

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Publications (5)


Fig. 1. Mesa model components: model, analysis and visualization.
Fig. 2. An illustration of how different activation schemes impact a model, in this case the Prisoner's Dilemma. Defecting agents are in red and cooperating agents are in blue. Each image is from the same step, but different activation schemes are used. (Color figure online)
Utilizing Python for Agent-Based Modeling: The Mesa Framework
  • Conference Paper
  • Full-text available

October 2020

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9,201 Reads

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152 Citations

Lecture Notes in Computer Science

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David Masad

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Mesa is an agent-based modeling framework written in Python. Originally started in 2013, it was created to be the go-to tool in for researchers wishing to build agent-based models with Python. Within this paper we present Mesa's design goals, along with its underlying architecture. This includes its core components: 1) the model (Model, Agent, Schedule, and Space), 2) analysis (Data Collector and Batch Runner) and the visualization (Visualization Server and Visualization Browser Page). We then discuss how agent-based models can be created in Mesa. This is followed by a discussion of applications and extensions by other researchers to demonstrate how Mesa design is decoupled and extensible and thus creating the opportunity for a larger decentralized ecosystem of packages that people can share and reuse for their own needs. Finally, the paper concludes with a summary and discussion of future development areas for Mesa.

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Mesa: An Agent-Based Modeling Framework

January 2015

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9,886 Reads

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202 Citations


International Relations

April 2014

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752 Reads

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15 Citations

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David Masad

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[...]

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The international community can be viewed as a set of networks manifested through various transnational activities. The availability of longitudinal data sets such as international arms trades and United Nations General Assembly (UNGA) allows for the study of state-driven interactions over time. In parallel to this top-down approach, the recent emergence of social media is fostering a bottom-up and citizen-driven avenue for international relations (IRs). The comparison of these two network types offers a new lens to study the alignment between states and their people. This article presents a network-driven approach to analyze communities as they are established through different forms of bottom-up (e.g., Twitter) and top-down (e.g., UNGA voting records and international arms trade records) IRs. By constructing and comparing different network communities, we were able to evaluate the similarities between state-driven and citizen-driven networks. In order to validate our approach we identified communities in UNGA voting records during and after the Cold War. Our approach showed that the similarity between UNGA communities during and after the Cold War was 0.55 and 0.81, respectively (in a 0–1 scale). To explore the state- versus citizen-driven interactions, we focused on the recent events in Syria within Twitter over a sample period of 1 month. The analysis of these data show a clear misalignment (0.25) between citizen-formed international networks and the ones established by the Syrian government (e.g., through its UNGA voting patterns).


Simulating International Energy Security

April 2014

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9 Reads

Lecture Notes in Computer Science

Energy security is placed at risk by exogenous supply shocks, in particular political crises and conflicts that disrupt resource extraction and transportation. In this paper, a computational model of the security of international crude oil supplies is described, and its output analyzed. The model consists of country agents, linked geographically and by a data-derived oil trade network. Countries stochastically experience crises, with probabilities and durations drawn randomly from data-fitted distributions. The effect of these crises on secure oil supplies is measured globally and by country, and the effect of conflict contagion and spare production capacity are also estimated. The model indicates that Russia, Eastern Europe, and much of the Global South are at the greatest risk of supply shocks, while American producers are at greatest risk of demand shocks. It estimates that conflict contagion decreases energy security slightly, while spare capacity has minimal effect.


Fig. 1. Example gene crossover 
Network Disruption and Recovery: Co-Evolution of Defender and Attacker in a Dynamic Game

January 2014

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63 Reads

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1 Citation

Studies in Computational Intelligence

The evolution of interactions between individuals or organizations are a central theme of complexity research. We aim at modeling a dynamic game on a network where an attacker and a defender compete in disrupting and reconnecting a network. The choices of how to attack and defend the network are governed by a Genetic Algorithm (GA) which is used to dynamically choose among a set of available strategies. Our analysis shows that the choice of strategy is particularly important if the resources available to the defender are slightly higher than the attackers'. The best strategies found through GAs by the attackers and defenders are based on betweenness centrality. Our results agree with previous literature assessing strategies for network attack and defense in a static context. However, our paper is one of the first ones to show how a GA approach can be applied in a dynamic game on a network. This research provides a starting-point to further explore strategies as we currently apply a limited set of strategies only. Codes are available at https://github.com/dmasad/NetAttack

Citations (3)


... The proposed simulation model has been implemented using Mesa [37], an ABM framework for Python. This framework maps the ABM paradigm into object-oriented programming in which each type of agent corresponds to a class where attributes define the state of the agent, and functions define agents' interactions. ...

Reference:

Enhancing healthcare infrastructure resilience through agent-based simulation methods
Utilizing Python for Agent-Based Modeling: The Mesa Framework

Lecture Notes in Computer Science

... In this paper, we introduce Casevo (a Cognitive Agents and Social Evolution Simulator), a multi-agent framework, focusing on the simulation of social interaction and communication based on complex networks. Casevo is built upon the Mesa framework with features for complex and realistic social behaviors and decision-making processes [5]. At the micro level, Casevo supports the construction of highly customized Agents with various features, including Role Insertion, Chain of Thought (CoT), Long-term and Short-term Memory Mechanisms, and so on. ...

Mesa: An Agent-Based Modeling Framework

... For example, the Centers for Disease Control and Prevention (CDC) utilized Twitter in the context of the 2009 H1N1 influenza outbreak to communicate critical issues to the public, and researchers conducted real-time content analysis of the Twitter content (Chew & Eysenbach, 2010;Terry, 2009). Furthermore, in 2014, the World Health Organization (WHO) used Twitter and other social networks to communicate risk information regarding the Ebola outbreak effectively and created two-way communication network circles in West Africa (Crooks et al., 2014). The findings of these studies suggest that Twitter is a channel for two-way communication where information can be disseminated from health authorities to the public. ...

International Relations