Open-ended Learning in Symmetric Zero-sum Games

Zero-sum games such as chess and poker are, abstractly, functions that evaluate pairs of agents, for example labeling them `winner' and `loser'. If the game is approximately transitive, then self-play generates sequences of agents of increasing strength. However, nontransitive games, such as rock-paper-scissors, can exhibit strategic cycles, and there is no longer a clear objective -- we want agents to increase in strength, but against whom is unclear. In this paper, we introduce a geometric framework for formulating agent objectives in zero-sum games, in order to construct adaptive sequences of objectives that yield open-ended learning. The framework allows us to reason about population performance in nontransitive games, and enables the development of a new algorithm (rectified Nash response, PSRO_rN) that uses game-theoretic niching to construct diverse populations of effective agents, producing a stronger set of agents than existing algorithms. We apply PSRO_rN to two highly nontransitive resource allocation games and find that PSRO_rN consistently outperforms the existing alternatives.Comment: ICML 2019, final versio

Shape-based clustering of synthetic Stokes profiles using k-means and k-Shape

The shapes of Stokes profiles contain much information about the atmospheric conditions that produced them. However, a variety of different atmospheric structures can produce very similar profiles. Thus, it is important for proper interpretation of observations to have a good understanding of how the shapes of Stokes profiles depend on the underlying atmosphere. An excellent tool in this regard is forward modeling, i.e. computing and studying synthetic spectra from realistic simulations of the solar atmosphere. Modern simulations routinely produce several hundred thousand spectral profiles per snapshot. With such numbers, it becomes necessary to use automated procedures in order to organize the profiles according to their shape. Here we illustrate the use of two complementary methods, k-means and k-Shape, to cluster similarly shaped profiles, and demonstrate how the resulting clusters can be combined with knowledge of the simulation's atmosphere to interpret spectral shapes. We generate synthetic Stokes profiles for the Ca II 854.2 nm line using the Multi3D code from a Bifrost simulation snapshot. We then apply the k-means and k-Shape clustering techniques to group the profiles together according to their shape. We show and compare the classes of profile shapes we retrieve from applying both k-means and k-Shape to our synthetic intensity spectra. We then show the structure of the underlying atmosphere for two particular classes of profile shapes retrieved by the clustering, and demonstrate how this leads to an interpretation for the formation of those profile shapes. Furthermore, we apply both methods to the subset of our profiles containing the strongest Stokes V signals, and demonstrate how k-Shape can be qualitatively better than k-means at retrieving complex profile shapes when using a small number of clusters.Comment: 12 pages, 9 figures. Accepted for publication in A&A. Abstract abridged for Arxi

From Mexico to Michigan and back: An international collaboration investigating primate behavior, ecology, and evolution from multiple perspectives

Evolutionary research benefits form the integration of laboratory and field components to determine factors and processes that affect the evolutionary trajectories of species. Our shared interest in understanding hybridization with genetic admixture as a process that may impact social, behavioral, and ecological features of primates, brought us together in a collaborative project aimed at addressing how vocal variation in two species of howler monkeys in Mexico affects and is affected by hybridization. To achieve this goal, we joined our academic expertise in studying primate genetics, ecology, and behavior under different natural and experimental conditions. We took advantage of decades of experience studying and handing wild howler monkeys for translocation projects to safely sample and study wild populations for this project. Here, we describe the history of our collaboration highlighting how our different perspectives, academic realities, and individual strengths built the foundation for our successful collaboration. We also share our perspectives on how this collaboration opened up new academic venues, broadened our individual perspectives on the integration of different research approaches to address a complex topic, and allowed us to recognize the strength of international collaboration.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149745/1/ajp22992_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149745/2/ajp22992.pd

Identifying wildlife reservoirs of neglected taeniid tapeworms : non-invasive diagnosis of endemic Taenia serialis infection in a wild primate population

Despite the global distribution and public health consequences of Taenia tapeworms, the life cycles of taeniids infecting wildlife hosts remain largely undescribed. The larval stage of Taenia serialis commonly parasitizes rodents and lagomorphs, but has been reported in a wide range of hosts that includes geladas (Theropithecus gelada), primates endemic to Ethiopia. Geladas exhibit protuberant larval cysts indicative of advanced T. serialis infection that are associated with high mortality. However, non-protuberant larvae can develop in deep tissue or the abdominal cavity, leading to underestimates of prevalence based solely on observable cysts. We adapted a non-invasive monoclonal antibody-based enzyme-linked immunosorbent assay (ELISA) to detect circulating Taenia spp. antigen in dried gelada urine. Analysis revealed that this assay was highly accurate in detecting Taenia antigen, with 98.4% specificity, 98.5% sensitivity, and an area under the curve of 0.99. We used this assay to investigate the prevalence of T. serialis infection in a wild gelada population, finding that infection is substantially more widespread than the occurrence of visible T. serialis cysts (16.4% tested positive at least once, while only 6% of the same population exhibited cysts). We examined whether age or sex predicted T. serialis infection as indicated by external cysts and antigen presence. Contrary to the female-bias observed in many Taenia-host systems, we found no significant sex bias in either cyst presence or antigen presence. Age, on the other hand, predicted cyst presence (older individuals were more likely to show cysts) but not antigen presence. We interpret this finding to indicate that T. serialis may infect individuals early in life but only result in visible disease later in life. This is the first application of an antigen ELISA to the study of larval Taenia infection in wildlife, opening the doors to the identification and description of infection dynamics in reservoir populations

Smooth markets: A basic mechanism for organizing gradient-based learners

With the success of modern machine learning, it is becoming increasingly important to understand and control how learning algorithms interact. Unfortunately, negative results from game theory show there is little hope of understanding or controlling general n-player games. We therefore introduce smooth markets (SM-games), a class of n-player games with pairwise zero sum interactions. SM-games codify a common design pattern in machine learning that includes (some) GANs, adversarial training, and other recent algorithms. We show that SM-games are amenable to analysis and optimization using first-order methods.Comment: 18 pages, 3 figure

Comparative clustering analysis of Ca II 854.2 nm spectral profiles from simulations and observations

We aim to compare and contrast the typical shapes of synthetic Ca II 854.2 nm spectra found in Bifrost simulations having different magnetic activity with the spectral shapes found in a quiet Sun observation from the Swedish 1-m Solar Telescope (SST). We use clustering techniques to extract the typical Ca II 854.2 nm profile shapes synthesized from Bifrost simulations with varying amounts of magnetic activity. We degrade the synthetic profiles to observational conditions and repeat the clustering, and we compare our synthetic results with actual observations. While the mean spectra for our high resolution simulations compare reasonably well with the observations, we find that there are considerable differences between the clusters of observed and synthetic intensity profiles, even after the synthetic profiles have been degraded. The typical absorption profiles from the simulations are both narrower and display a steeper transition from the inner wings to the line core. Furthermore, even in our most quiescent simulation we find a far larger fraction of profiles with local emission around the core, or other exotic profile shapes, than in the observations. Looking into the atmospheric structure for a selected set of synthetic clusters, we find distinct differences in the temperature stratification for the clusters most and least similar to the observations. The narrow and steep profiles are associated with either weak gradients in temperature, or temperatures rising to a local maximum in the line wing forming region before sinking to a minimum in the line core forming region. The profiles that display less steep transitions show extended temperature gradients that are steeper in the range $-3 \lesssim \log \tau_{5000} \lesssim -1$.Comment: Accepted for publication in A&A. Abstract abridged for Arxi

A multiscale framework for disentangling the roles of evenness, density, and aggregation on diversity gradients

Ecology published by Wiley Periodicals LLC on behalf of Ecological Society of America Disentangling the drivers of diversity gradients can be challenging. The Measurement of Biodiversity (MoB) framework decomposes scale-dependent changes in species diversity into three components of community structure: species abundance distribution (SAD), total community abundance, and within-species spatial aggregation. Here we extend MoB from categorical treatment comparisons to quantify variation along continuous geographic or environmental gradients. Our approach requires sites along a gradient, each consisting of georeferenced plots of abundance-based species composition data. We demonstrate our method using a case study of ants sampled along an elevational gradient of 28 sites in a mixed deciduous forest of the Great Smoky Mountains National Park, USA. MoB analysis revealed that decreases in ant species richness along the elevational gradient were associated with decreasing evenness and total number of species, which counteracted the modest increase in richness associated with decreasing spatial aggregation along the gradient. Total community abundance had a negligible effect on richness at all but the finest spatial grains, SAD effects increased in importance with sampling effort, and the aggregation effect had the strongest effect at coarser spatial grains. These results do not support the more-individuals hypothesis, but they are consistent with a hypothesis of stronger environmental filtering at coarser spatial grains. Our extension of MoB has the potential to elucidate how components of community structure contribute to changes in diversity along environmental gradients and should be useful for a variety of assemblage-level data collected along gradients