Colorado: Round 1 - State-Level Field Network Study of the Implementation of the Affordable Care Act

This report is part of a series of 21 state and regional studies examining the rollout of the ACA. The national network -- with 36 states and 61 researchers -- is led by the Rockefeller Institute of Government, the public policy research arm of the State University of New York, the Brookings Institution, and the Fels Institute of Government at the University of Pennsylvania.Colorado is one of fourteen states and the District of Columbia that elected to operate a state-based health insurance exchange and to expand Medicaid in 2014 as part of the rollout of the Affordable Care Act (ACA). These decisions are consistent with Colorado's approach to health care reform. Before the ACA was signed into law in 2010, the state had made incremental expansions in Medicaid eligibility and laid the groundwork for an insurance marketplace

Issue Brief: The Magnitude of Underinsurance in Colorado

As health care reform gets implemented, there are many questions to be answered, including to what extent federal reform will address the adequacy of health coverage. Prepared for The Colorado Trust by the Colorado Health Institute, this Issue Brief is based on data from the 2008-09 Colorado Household Survey (COHS). Key findings show that 650,000 Coloradans are underinsured -- almost the same number as uninsured residents -- and, although individuals over 65 years old usually have Medicare, the highest rate of underinsurance occurs among this age group. As well, underinsured Coloradans are more likely to forego medical care and/or report problems paying medical bills than those Coloradans deemed adequately insured

CPPN2GAN: Combining Compositional Pattern Producing Networks and GANs for Large-Scale Pattern Generation

Generative Adversarial Networks (GANs) are proving to be a powerful indirect genotype-to-phenotype mapping for evolutionary search, but they have limitations. In particular, GAN output does not scale to arbitrary dimensions, and there is no obvious way of combining multiple GAN outputs into a cohesive whole, which would be useful in many areas, such as the generation of video game levels. Game levels often consist of several segments, sometimes repeated directly or with variation, organized into an engaging pattern. Such patterns can be produced with Compositional Pattern Producing Networks (CPPNs). Specifically, a CPPN can define latent vector GAN inputs as a function of geometry, which provides a way to organize level segments output by a GAN into a complete level. This new CPPN2GAN approach is validated in both Super Mario Bros. and The Legend of Zelda. Specifically, divergent search via MAP-Elites demonstrates that CPPN2GAN can better cover the space of possible levels. The layouts of the resulting levels are also more cohesive and aesthetically consistent.Comment: GECCO 2020. arXiv admin note: text overlap with arXiv:2004.0015