Bharathy, Gnana K.
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PublicationHolistically Evaluating Agent Based Social System Models(2012-01-01) Bharathy, Gnana K.; Silverman, Barry G.The philosophical perspectives on model evaluation can be broadly classified into reductionist/logical positivist and relativist/holistic. In this paper, we outline some of our past efforts in, and challenges faced during, evaluating models of social systems with cognitively detailed agents. Owing to richness in the model, we argue that the holistic approach and consequent continuous improvement are essential to evaluating complex social system models such as these. A social system built primarily of cognitively detailed agents can provide multiple levels of correspondence, both at observable and abstract aggregated levels. Such a system can also pose several challenges, including large feature spaces, issues in information elicitation with database, experts and news feeds, counterfactuals, fragmented theoretical base, and limited funding for validation. We subscribe to the view that no model can faithfully represent reality, but detailed, descriptive models are useful in learning about the system and bringing about a qualitative jump in understanding of the system it attempts to model – provided they are properly validated. Our own approach to model evaluation is to consider the entire life cycle and assess the validity under two broad dimensions of (1) internally focused validity/quality achieved through structural, methodological, and ontological evaluations; and (2) external validity consisting of micro validity, macro validity, and qualitative, causal and narrative validity. In this paper, we also elaborate on selected validation techniques that we have employed in the past. We recommend a triangulation of multiple validation techniques, including methodological soundness, qualitative validation techniques, such as face validation by experts and narrative validation, and formal validation tests, including correspondence testing. PublicationWhat is a Good Pattern of Life Model? Guidance for Simulations(2018-08-01) Silverman, Barry G; Bharathy, Gnana K.; Weyer, NathanWe have been modeling an ever-increasing scale of applications with agents that simulate the pattern of life (PoL) and real-world human behaviors in diverse regions of the world. The goal is to support sociocultural training and analysis. To measure progress, we propose the definition of a measure of goodness for such simulated agents, and review the issues and challenges associated with first-generation (1G) agents. Then we present a second generation (2G) agent hybrid approach that seeks to improve realism in terms of emergent daily activities, social awareness, and micro-decision making in simulations. We offer a PoL case study with a mix of 1G and 2G approaches that was able to replace the pucksters and avatar operators needed in large-scale immersion exercises. We conclude by observing that a 1G PoL simulation might still be best where large-scale, pre-scripted training scenarios will suffice, while the 2G approach will be important for analysis or if it is vital to learn about adaptive opponents or unexpected or emergent effects of actions. Lessons are shared about ways to blend 1G and 2G approaches to get the best of each. PublicationValidating Agent Based Social Systems Models(2010-12-05) Bharathy, Gnana K.; Silverman, Barry GValidating social systems is not a trivial task. The paper outlines some of our past efforts in validating models of social systems with cognitively detailed agents. It also presents some of the challenges faced by us. A social system built primarily of cognitively detailed agents can provide multiple levels of correspondence, both at observable and abstract aggregated levels. Such a system can also pose several challenges including large feature spaces, issues in information elicitation with database, experts and news feeds, counterfactuals, fragmented theoretical base, and limited funding for validation. Our own approach to validity assessment is to consider the entire life cycle and assess the validity under four broad dimensions of methodological validity, internal validity, external validity and qualitative, causal and narrative validity. In the past, we have employed a triangulation of multiple validation techniques, including face validation as well as formal validation tests including correspondence testing. PublicationA Systems Approach to Healthcare: Agent-based Modeling, Community Mental Health, and Population Well-being(2014-09-13) Silverman, Barry G.; Bharathy, Gnana K.; Hanrahan, Nancy; Gordon, Kim; Johnson, DanPurpose Explore whether agent-based modeling and simulation can help healthcare administrators discover interventions that increase population wellness and quality of care while, simultaneously, decreasing costs. Since important dynamics often lie in the social determinants outside the health facilities that provide services, this study thus models the problem at three levels (individuals, organizations, and society). Methods The study explores the utility of translating an existing (prize winning) software for modeling complex societal systems and agent's daily life activities (like a Sim City style of software), into a desired decision support system. A case study tests if the 3 levels of system modeling approach is feasible, valid, and useful. The case study involves an urban population with serious mental health and Philadelphia's Medicaid population (n = 527,056), in particular. Results Section 3 explains the models using data from the case study and thereby establishes feasibility of the approach for modeling a real system. The models were trained and tuned using national epidemiologic datasets and various domain expert inputs. To avoid co-mingling of training and testing data, the simulations were then run and compared (Section 4.1) to an analysis of 250,000 Philadelphia patient hospital admissions for the year 2010 in terms of re-hospitalization rate, number of doctor visits, and days in hospital. Based on the Student t-test, deviations between simulated vs. real world outcomes are not statistically significant. Validity is thus established for the 2008–2010 timeframe. We computed models of various types of interventions that were ineffective as well as 4 categories of interventions (e.g., reduced per-nurse caseload, increased check-ins and stays, etc.) that result in improvement in well-being and cost. Conclusions The 3 level approach appears to be useful to help health administrators sort through system complexities to find effective interventions at lower costs.