Krasnow Institute for Advanced Study
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The Krasnow Institute seeks to expand understanding of mind, brain, and intelligence by conducting research at the intersection of the separate fields of cognitive psychology, neurobiology, and the computer-driven study of artificial intelligence and complex adaptive systems. These separate disciplines increasingly overlap and promise progressively deeper insight into human thought processes. The Institute also examines how new insights from cognitive science research can be applied for human benefit in the areas of mental health, neurological disease, education, and computer design.
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Browsing Krasnow Institute for Advanced Study by Subject "Agent-based modeling"
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Item A Computational Theory of Endogenous Norm Change: The NormSim Agent-Based Model in MASON(2011-08-22) Rouleau, Mark D.; Rouleau, Mark D.; Cioffi-Revilla, ClaudioThe current study presents the NormSim Agent-Based Model in MASON. NormSim conducts a computational analysis of the International Relations theory of constructivism. NormSim explores the metastable dynamics of norms through the interactions of heterogeneous agents embedded within a complex social system. The goal is to explain how the social complexity of international relations generates metastability. The use of ABM and the MASON simulation toolkit make it possible to explore this process from a formal experimental perspective. This is advantageous for constructivist research that typically must rely on qualitative analysis alone to justify complex theoretical assumptions. NormSim demonstrates the use of ABM to test the logical consistency of constructivist claims. It also extends constructivist logic to better understand why international norms lead to complex conformity patterns and long run systemic change. NormSim provides a general computational theory to explain this phenomenon.Item A General Social Agent-Based Model of Opinion Dynamics with Applications to STEM Education and Radicalization(2016) Harrison, Joseph Francis; Harrison, Joseph Francis; Cioffi-Revilla, ClaudioMany aspects of our society are affected by how opinions change and ideology spreads (e.g., interest in STEM and political radicalization), but the underlying processes are not well understood. Previous attempts at modeling these phenomena have suffered from a lack of empirical data and/or insufficient grounding in social-psychological theory. Moreover, the field of opinion dynamics would benefit from a broader view of the discipline that captures the commonalities between different domains.Item Agents in Conflict: Comparative Agent-Based Modeling of International Crises and ConflictsMasad, David P.; Masad, David P.; Axtell, RobertInter-state conflicts are a key area of study in international relations, and have been approached with a variety of techniques, from case studies of individual conflicts, to formal analysis of abstract models and statistical investigations of all such conflicts. In particular, there are a variety of theories as to how states make decisions in the face of conflicts -- such as when to threaten force, when to follow through, and when to capitulate to an opponent's demand. Some scholars have argued that states may be viewed as rational decisionmakers, while others emphasize the role of psychological biases affecting individual leaders. Decisionmaking is challenging to study in part because of its complexity: the decisionmakers may not just be individuals but organizations, following internal procedures and reflecting institutional memory. Furthermore, the decisions are often believed to be strategic, reflect- ing the decisionmakers' anticipation of multiple other actors' potential responses to each possible decision. In this dissertation, I demonstrate that agent-based models (ABMs) provide a powerful tool to address this complexity, and advance their use as a bridge between different method- ologies. Agents in ABMs can be used to represent countries and endowed with a variety of internal decisionmaking models which can operationalize a variety of theories drawn from case studies, psychological experiments or game-theoretic analysis. The specific decision model agents utilize may be changed without altering the sub-models governing how the agents interact with one another. This allows us to simulate the same overall interactions utilizing different decisionmaking theories and observe how the outcomes differ. Furthermore, if these interactions correspond to real-world events, we may directly see how much explanatory or predictive power the outputs of the model variants provide. If one variant's outputs correspond closer to the empirical data, it provides evidence supporting that variant's underlying theory. I implement two agent-based models, extending well-established prior models of international conflict: the International Interaction Game (Bueno de Mesquita and Lalman, 1992) and the Expected Utility Model (Bueno de Mesquita, 2002). For each, I start with their original agent decisionmaking models, and develop several variants grounded in relevant theories. I then instantiate the models with historic, empirically-derived data and run them forward to generate sets of simulated outcomes, which I compare to empirical data on the relevant time periods. I find that non-rational models of decisionmaking in the International Interaction Game provide similar explanatory power to the purely rational model, and yield rich satisficing behavior absent in the original model. I also find that the Expected Utility Model variant implementing a Schelling (1966)-inspired model of coercion yields richer dynamics and greater explanatory power than the original model. In addition to providing evidence in support of particular theories and hypotheses, this work demonstrates the power of the comparative modeling methodology in studying international conflict. Future work will involve adding more statistical controls to the model output analysis, comparative analysis between the outputs of the two overall models, and extension of the decisionmaking models for each. The same methodology may also be expanded to other formal and computational models of international relations, and social science more broadly.Item Climate Change and the Potential for Conflict and Extreme Migration in the Andes: A Computational Approach for Interdisciplinary Modeling and Anticipatory Policy-Making(2015) Magallanes, Jose Manuel; Magallanes, Jose Manuel; Cioffi, ClaudioI present an agent-based model to support the thesis that extreme migration and social conflict can emerge by simply extending the current social and natural conditions, and by replicating simple mechanisms at the individual level. To carry out this work, every available information on water supply and demand has been collected and organized using official data sources, producing a baseline dated in 2011; and the basic demographics of the population has been implemented using the last official census (2007). Based on these data, many computations have been made to find, calibrate and represent the trends in population growth and water balance. For the basic mechanisms at the individual level, field work guided both by theoretical considerations and ethnographic findings has been done. A key assumption on the processing of information, not identified from the field work, has been introduced via a Bayesian belief updating mechanism.Item Computational Modeling of Climate Change, Large-Scale Land Acquisition, and Household Dynamics in Southern Ethiopia(2013-08) Hailegiorgis, Atesmachew Bizuwerk; Hailegiorgis, Atesmachew Bizuwerk; Cioffi-Revilla, ClaudioCOMPUTATIONAL MODELING OF CLIMATE CHANGE, LARGE-SCALE LAND ACQUISITION, AND HOUSEHOLD DYNAMICS IN SOUTHERN ETHIOPIAItem Using Social Media Content to Inform Agent-based Models for Humanitarian Crisis Response(2014-05) Wise, Sarah; Wise, Sarah; Crooks, Andrew T.Crisis response is a time-sensitive problem with multiple concurrent and interacting subprocesses, applied around the world in a wide range of contexts and with access to varying levels of resources. The movement of individuals with their shifting patterns of need and, frequently, disrupted normal support systems pose challenges to responders trying to understand what is needed, where, and when. Unfortunately, crises frequently occur in parts of the world that lack the infrastructure to respond to them and the information to inform responders where to target their efforts. In light of these challenges, researchers can make use of new data sources and technologies, combining the information products with simulation techniques to gain knowledge of the situation and to explore the various ways in which a crisis may develop. These new data sources - including social media such as Twitter and volunteered geographic information (VGI) from groups such as OpenStreetMap - can be combined with authoritative data sources in order to create rich, synthetic datasets, which may in turn be subjected to processes such as sentiment analysis and social network analysis. Further, these datasets can be transformed into information which supports powerful agent- based models (ABM). Such models can capture the behavior of heterogeneous individuals and their decision-making process, allowing researchers to explore the emergent dynamics of crisis situations. To that end, this research explores the gathering, cleaning, and synthesis of diverse data sources as well as the information which can be extracted from such synthetic data sources. Further, the work presents a rich, behaviorally complex agent-based model of an evacuation effort. The case study deals with the 2012 Colorado Wildfires, which threatened the city of Colorado Springs and prompted the evacuation of over 28,000 persons over the course of four days. The model itself explores how a synthetic population with automatically generated synthetic social networks communicates about and responds to the developing crisis, utilizing real evacuation order information as well as a model of wildfire development to which the individual agents respond. This research contributes to the study of data synthesis, agent-based modeling, and crisis development.