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 Author "Axtell, Robert"
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Item A Computational Social Science Approach to the Social Determinants of Cancer(2016) Metgher, Cristina; Metgher, Cristina; Axtell, RobertCancer is a complex system of systems - in which heterogeneous actors interact dynamically with each other and with the environment across time. It is the second leading cause of death in the U. S. after cardiovascular disease, striking people from all occupations and backgrounds. The U. S. President Nixon declared the “War on Cancer” in 1971. Since then, much progress has been made towards understanding this disease. However, due to the reductionist thinking that has been predominant in cancer research for the last decades, the mortality rates due to cancer have hardly changed.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 An Essay on Micro Heterogeneity and the Evolution of InequalityShin, Hyungsik; Shin, Hyungsik; Axtell, RobertThe level of inequality has increased over the past several decades and reached at the historically high level in many developed countries. Yet, the traditional theory of supply and demand in labor has failed to elucidate the emergence of prevailing inequality from bottom up. In fact, its scope on inequality has been limited and overlooked the emergence of inequality through interactions of heterogeneous sub-systems in micro level. In this dissertation, therefore, I have used Agent-based Models as an alternative to traditional methods to understand the evolution of inequality given micro heterogeneity and bridge the gap between the theory and real world. In the first two chapters, I have studied how behaviors of ill-motivated heterogeneous individuals cause inequality to rise and severe crises. In the first chapter, it has focused to compare and contrast macro behaviors such as inequality and growth when the compen- sation system is vulnerable to free riding or not in an otherwise identical economy. The model results have demonstrated that if the compensation is ill-defined, individuals became selfish "free riders" and the economy became volatile hence experienced constantly rising inequality followed by crises. In the second chapter, it has examined the effect of such ill-defined compensation system on inequality and growth via consumption channels -- demand-driven recession. The simulation outcomes have revealed that even a mild income concentration in the hands of a few in the beginning could cause a terrible economic recession eventually because such an income squeeze led a decrease in consumption of the poor and middle class which in turns, drags down a whole economy. It has confirmed the wide-spreading belief that if the poor and middle class cannot afford to buy goods and services, it causes a collapse of an economy eventually. In the last chapter, I have explored that when information -- characteristics -- about goods is the object of preference rather than goods per se, contrast to the traditional theory of supply and demand, how such a change in the preference object affects market equilibrium and inequality in a barter-based economy. The simulation results have demonstrated that, depending on the ratio of characteristics of goods, even after finitely many numbers of trades, MRSs of goods do not necessarily converge to the optimal level. In other words, many agents are not content with their after-trade endowments but can't be helped because existing goods do not suit them to be Pareto optimal. When it comes to inequality, GINI coefficient, an index for measuring the level of inequality is limited to capture dynamics of the change in wealth over trades within a period. Thus, it is not clear that the change in the object of preference affects the evolution of inequality over trades as well as over time.Item Explaining Box Office Performance from the Bottom Up: Data, Theories and Models(2016) Russo, Holly Ann; Russo, Holly Ann; Axtell, RobertEvery week, there are more than 50 movies playing in theaters from which movie-goers can choose. Analyses of the relative box office success of these films shows that it is Pareto-distributed, with roughly 20% of them earning 80% of the overall revenue. Arthur De Vany studied the potential causes of this ‘winner-take-all’ distribution through equation-based analyses, and theorized that the Pareto-distributed box office revenues we observe emerge from the micro-level complex adaptive behavior of movie-goers with imperfect information.