Curiosity search for non-equilibrium behaviors in a dynamically learned order parameter space

Exploring the spectrum of novel behaviors a physical system can produce can be a labor-intensive task. Active learning is a collection of iterative sampling techniques developed in response to this challenge. However, these techniques often require a pre-defined metric, such as distance in a space of known order parameters, in order to guide the search for new behaviors. Order parameters are rarely known for non-equilibrium systems \textit{a priori}, especially when possible behaviors are also unknown, creating a chicken-and-egg problem. Here, we combine active and unsupervised learning for automated exploration of novel behaviors in non-equilibrium systems with unknown order parameters. We iteratively use active learning based on current order parameters to expand the library of known behaviors and then relearn order parameters based on this expanded library. We demonstrate the utility of this approach in Kuramoto models of coupled oscillators of increasing complexity. In addition to reproducing known phases, we also reveal previously unknown behavior and related order parameters

Cascading training down into the classroom: The need for parallel planning

Cascade models of in-service training are widely considered to be a cost effective means of introducing educational change to large numbers of teachers. Data from 511 teachers completing a cascade training programme that introduced current ideas about and procedures for teaching English to young learners, suggests that provision of training alone is no guarantee that cascade training aims will actually be applied in classrooms. The paper considers implications for cascade projects, suggesting that planning needs to be a parallel process if an adequate return on outlay, in the sense of teachers applying skills introduced in training in their classrooms, is to be achieved

Sexual selection protects against extinction

Reproduction through sex carries substantial costs, mainly because only half of sexual adults produce offspring. It has been theorised that these costs could be countered if sex allows sexual selection to clear the universal fitness constraint of mutation load. Under sexual selection, competition between (usually) males, and mate choice by (usually) females create important intraspecific filters for reproductive success, so that only a subset of males gains paternity. If reproductive success under sexual selection is dependent on individual condition, which depends on mutation load, then sexually selected filtering through ‘genic capture’ could offset the costs of sex because it provides genetic benefits to populations. Here, we test this theory experimentally by comparing whether populations with histories of strong versus weak sexual selection purge mutation load and resist extinction differently. After evolving replicate populations of the flour beetle Tribolium castaneum for ~7 years under conditions that differed solely in the strengths of sexual selection, we revealed mutation load using inbreeding. Lineages from populations that had previously experienced strong sexual selection were resilient to extinction and maintained fitness under inbreeding, with some families continuing to survive after 20 generations of sib × sib mating. By contrast, lineages derived from populations that experienced weak or non-existent sexual selection showed rapid fitness declines under inbreeding, and all were extinct after generation 10. Multiple mutations across the genome with individually small effects can be difficult to clear, yet sum to a significant fitness load; our findings reveal that sexual selection reduces this load, improving population viability in the face of genetic stress

Reports of the AAAI 2019 spring symposium series

Applications of machine learning combined with AI algorithms have propelled unprecedented economic disruptions across diverse fields in industry, military, medicine, finance, and others. With the forecast for even larger impacts, the present economic impact of machine learning is estimated in the trillions of dollars. But as autonomous machines become ubiquitous, recent problems have surfaced. Early on, and again in 2018, Judea Pearl warned AI scientists they must "build machines that make sense of what goes on in their environment," a warning still unheeded that may impede future development. For example, self-driving vehicles often rely on sparse data; self-driving cars have already been involved in fatalities, including a pedestrian; and yet machine learning is unable to explain the contexts within which it operates

International Coercion, Emulation and Policy Diffusion: Market-Oriented Infrastructure Reforms, 1977-1999

Why do some countries adopt market-oriented reforms such as deregulation, privatization and liberalization of competition in their infrastructure industries while others do not? Why did the pace of adoption accelerate in the 1990s? Building on neo-institutional theory in sociology, we argue that the domestic adoption of market-oriented reforms is strongly influenced by international pressures of coercion and emulation. We find robust support for these arguments with an event-history analysis of the determinants of reform in the telecommunications and electricity sectors of as many as 205 countries and territories between 1977 and 1999. Our results also suggest that the coercive effect of multilateral lending from the IMF, the World Bank or Regional Development Banks is increasing over time, a finding that is consistent with anecdotal evidence that multilateral organizations have broadened the scope of the “conditionality” terms specifying market-oriented reforms imposed on borrowing countries. We discuss the possibility that, by pressuring countries into policy reform, cross-national coercion and emulation may not produce ideal outcomes.http://deepblue.lib.umich.edu/bitstream/2027.42/40099/3/wp713.pd

Preclinical evidence implicating corticotropin-releasing factor signaling in ethanol consumption and neuroadaptation

The results of many studies support the influence of the corticotropin-releasing factor (CRF) system on ethanol (EtOH) consumption and EtOH-induced neuroadaptations that are critical in the addiction process. This review summarizes the preclinical data in this area after first providing an overview of the components of the CRF system. This complex system involves hypothalamic and extra-hypothalamic mechanisms that play a role in the central and peripheral consequences of stressors, including EtOH and other drugs of abuse. In addition, several endogenous ligands and targets make up this system and show differences in their involvement in EtOH drinking and in the effects of chronic or repeated EtOH treatment. In general, genetic and pharmacological approaches paint a consistent picture of the importance of CRF signaling via type 1 CRF receptors (CRF1) in EtOH-induced neuroadaptations that result in higher levels of intake, encourage alcohol seeking during abstinence and alter EtOH sensitivity. Furthermore, genetic findings in rodents, non-human primates and humans have provided some evidence of associations of genetic polymorphisms in CRF-related genes with EtOH drinking, although additional data are needed. These results suggest that CRF1 antagonists have potential as pharmacotherapeutics for alcohol use disorders. However, given the broad and important role of these receptors in adaptation to environmental and other challenges, full antagonist effects may be too profound and consideration should be given to treatments with modulatory effects.The authors were supported by the Department of Veterans Affairs; NIH NIAAA grants P60AA010760, R24AA020245 and U01AA013519 and NIH NIDA grant P50DA018165, during the writing of this manuscript. The authors have no financial conflict of interest to disclose

An Experimental Field Study of Delayed Density Dependence in Natural Populations of Aedes albopictus

Aedes albopictus, a species known to transmit dengue and chikungunya viruses, is primarily a container-inhabiting mosquito. The potential for pathogen transmission by Ae. albopictus has increased our need to understand its ecology and population dynamics. Two parameters that we know little about are the impact of direct density-dependence and delayed density-dependence in the larval stage. The present study uses a manipulative experimental design, under field conditions, to understand the impact of delayed density dependence in a natural population of Ae. albopictus in Raleigh, North Carolina. Twenty liter buckets, divided in half prior to experimentation, placed in the field accumulated rainwater and detritus, providing oviposition and larval production sites for natural populations of Ae. albopictus. Two treatments, a larvae present and larvae absent treatment, were produced in each bucket. After five weeks all larvae were removed from both treatments and the buckets were covered with fine mesh cloth. Equal numbers of first instars were added to both treatments in every bucket. Pupae were collected daily and adults were frozen as they emerged. We found a significant impact of delayed density-dependence on larval survival, development time and adult body size in containers with high larval densities. Our results indicate that delayed density-dependence will have negative impacts on the mosquito population when larval densities are high enough to deplete accessible nutrients faster than the rate of natural food accumulation

Reconstructed Dynamics of Rapid Extinctions of Chaparral-Requiring Birds in Urban Habitat Islands

The distribution of native, chaparral-requiring bird species was determined for 37 isolated fragments of canyon habitat ranging in size from 0.4 to 104 hectares in coastal, urban San Diego County, California The area of chaparral habitat and canyon age (time since isolation of the habitat fragment) explains most of the variation in the number of chaparral-requiring bird species. In addition, the distribution of native predators may influence species number. There is statistical evidence that coyotes control the populations of smaller predators such as foxes and domestic cats. The absence of coyotes may lead to higher levels of predation by a process of mesopredator release. The distance of canyons from other patches of chaparral habitat does not add significantly to the explained variance in chaparral-requiring species number–probably because of the virtual inability of most chaparral-requiring species to disperse through developed areas and nonscrub habitats. These results and other lines of evidence suggest that chaparral-requiring birds in isolated canyons have very high rates of extinction, in part because of their low vagility. The best predictors of vulnerability of the individual species are their abundances (densities) in undisturbed habitat and their body sizes; together these two variables account for 95 percent of the variation in canyon occupancy. A hypothesis is proposed to account for the similarity between the steep slopes of species-area curves for chaparral-requiring birds and the slopes for some forest birds on small islands or in habitat fragments. The provision of corridors appears to be the most effective design and planning feature for preventing the elimination of chaparral-requiring species in a fragmented landscape.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74761/1/j.1523-1739.1988.tb00337.x.pd