A comparison of open and closed loop applications of the minimum distance guidance technique

A comparison is made of open and closed loop applications of a second order guidance algorithm, using the minimum distance strategy. A nonlinear reoptimization procedure is used as the ideal guidance history. The system model used for the comparison is a low-thrust vehicle performing a minimum time, three-dimensional, heliocentric Earth-Mars transfer. For the example problem considered, closed loop guidance proves to be much more accurate on satisfaction of the final state than the open loop procedure. On the other hand, closed loop guidance proves to be much more vulnerable to perturbation by highly nonlinear regions in the trajectory. Finally, the results indicate that for this problem the best loop closure interval is at each integration step, about one day, or more often, if possible

Optimistic Agents are Asymptotically Optimal

We use optimism to introduce generic asymptotically optimal reinforcement learning agents. They achieve, with an arbitrary finite or compact class of environments, asymptotically optimal behavior. Furthermore, in the finite deterministic case we provide finite error bounds.Comment: 13 LaTeX page

Distortions to Agricultural Incentives in Australia and New Zealand

In 1990, Australia and New Zealand were ranked around 25th and 35th in terms of GNP per capita, having been the highest-income countries in the world one hundred years earlier. The poor performance over that long period contrasts markedly with that of the past 15 years, when these two economies out-performed most other high-income countries. This difference in growth performance is due to major economic policy reforms during the past two to three decades. We provide new evidence on the extent of governmental distortions to agricultural incentives in particular in the two economies since the late 1940s, both directly and indirectly (and negatively) via manufacturing protection.Distorted incentives, agricultural and trade policy reform, Agricultural and Food Policy, F13, F14, Q17, Q18,

Changing Patterns of Sexual Risk Behavior Among London Gay Men: 1998-2008

Objectives: To examine changes in the sexual behavior of London gay men between 1998 and 2008. Methods: Gay men using London gyms were surveyed annually between 1998 and 2005, and again in 2008 (n = 6064; range, 482–834 per year). Information was collected on human immunodeficiency virus (HIV) status of the respondent, unprotected anal intercourse (UAI) in the previous 3 months, type (main or casual) and HIV status of partner for UAI. Nonconcordant UAI (ncUAI) was defined as UAI with a partner of unknown or discordant HIV status. Concordant UAI (cUAI) was defined as UAI with a partner of the same HIV status (“serosorting”). Results: Between 1998 and 2008, the percentage of men reporting UAI increased from 24.3% to 36.6% (P = 0.07). This overall increase concealed important differences between nonconcordant and concordant UAI. While the percentage of men engaging in cUAI increased steadily between 1998 and 2008 (9.8%, 20.8%; P = 0.01), the percentage reporting ncUAI increased between 1998 and 2001 (14.5%, 23.7%; P < 0.001), decreased between 2001 and 2005 (23.7%, 15.6%; P < 0.001), and then leveled off between 2005 and 2008 (15.6%, 15.7%; P = 0.2). However, the percentage of men reporting ncUAI with a main partner increased between 2005 and 2008 for HIV-positive men (2.5%, 8.1%; P < 0.05) and HIV negative men (2.1%, 5.5%; P = 0.06). While the percentage of HIV negative men who reported cUAI with a main partner (i.e., serosorting) increased between 1998 and 2008 (12.4%, 21.1%; P < 0.05), less than half established seroconcordance by testing together. Conclusions: The patterns of sexual behavior among London's gay men between 1998 and 2008 were dynamic and complex. Our data suggest that HIV risk with a main partner and HIV testing among couples should be given greater priority by health promotion programmes

Universal knowledge-seeking agents for stochastic environments

We define an optimal Bayesian knowledge-seeking agent, KL-KSA, designed for countable hypothesis classes of stochastic environments and whose goal is to gather as much information about the unknown world as possible. Although this agent works for arbitrary countable classes and priors, we focus on the especially interesting case where all stochastic computable environments are considered and the prior is based on Solomonoff’s universal prior. Among other properties, we show that KL-KSA learns the true environment in the sense that it learns to predict the consequences of actions it does not take. We show that it does not consider noise to be information and avoids taking actions leading to inescapable traps. We also present a variety of toy experiments demonstrating that KL-KSA behaves according to expectation

Labor Trafficking Victimization among Farmworkers in North Carolina: Role of Demographic Characteristics and Acculturation

Human trafficking is a hidden domestic and international problem of unknown numbers and unsubstantiated estimates. Most research on labor trafficking has focused on known cases through conducting stakeholder interviews and reviewing police and court case files. This limited prior research suggests that demographic characteristics and level of acculturation may impact one’s risk for labor trafficking victimization. However, these relationships have not been consistently demonstrated. The current research explores two primary research questions: (1) how prevalent is labor trafficking and other labor exploitation among farmworkers in North Carolina; and (2) do individual-level characteristics or circumstances place a person at greater risk of labor trafficking or other labor exploitation. This was accomplished by conducting 380 inperson interviews with migrant farmworkers in North Carolina. We used three strategies to identify migrant farmworkers: (1) attendance at community events; (2) lists of labor camps known to advocacy organizations; and (3) other public venues farmworkers visit. Based on descriptive statistics and a logistic regression analysis, we present results on the extent of farmworker abuse and exploitation, and discuss future research in this area

Sequential Extensions of Causal and Evidential Decision Theory

Moving beyond the dualistic view in AI where agent and environment are separated incurs new challenges for decision making, as calculation of expected utility is no longer straightforward. The non-dualistic decision theory literature is split between causal decision theory and evidential decision theory. We extend these decision algorithms to the sequential setting where the agent alternates between taking actions and observing their consequences. We find that evidential decision theory has two natural extensions while causal decision theory only has one.Comment: ADT 201

Cognitive biases to healthy and unhealthy food words predict change in BMI

The current study explored the predictive value of cognitive biases to food cues (assessed by emotional Stroop and dot probe tasks) on weight change over a 1-year period. This was a longitudinal study with undergraduate students (N = 102) living in shared student accommodation. After controlling for the effects of variables associated with weight (e.g., physical activity, stress, restrained eating, external eating, and emotional eating), no effects of cognitive bias were found with the dot probe. However, for the emotional Stroop, cognitive bias to unhealthy foods predicted an increase in BMI whereas cognitive bias to healthy foods was associated with a decrease in BMI. Results parallel findings in substance abuse research; cognitive biases appear to predict behavior change. Accordingly, future research should consider strategies for attentional retraining, encouraging individuals to reorient attention away from unhealthy eating cues

The diverse nature of island isolation and its effect on land bridge insular faunas

Aim: Isolation is a key factor in island biology. It is usually defined as the distance to the geographically nearest mainland, but many other definitions exist. We explored how testing different isolation indices affects the inference of impacts of isolation on faunal characteristics. We focused on land bridge islands and compared the relationships of many spatial and temporal (i.e., through time) isolation indices with community‐, population‐ and individual‐level characteristics (species richness, population density and body size, respectively). Location: Aegean Sea islands, Greece. Time period: Current. Taxon: Many animal taxa. Methods: We estimated 21 isolation indices for 205 islands and recorded species richness data for 15 taxa (invertebrates and vertebrates). We obtained body size data for seven lizard species and population density data for three. We explored how well indices predict each characteristic, in each taxon, by conducting a series of ordinary least squares regressions (controlling for island area when needed) and a meta‐analysis. Results: Isolation was significantly (and negatively) associated with species richness in 10 of 15 taxa. It was significantly (and positively) associated with body size in only one of seven species and was not associated with population density. The effect of isolation on species richness was much weaker than that of island area, regardless of the index tested. Spatial indices generally out‐performed temporal indices, and indices directly related to the mainland out‐performed those related mainly to neighbouring islands. No index was universally superior to others, including the distance to the geographically nearest mainland. Main conclusions: The choice of index can alter our perception of the impacts of isolation on biological patterns. The nearly automatic, ubiquitous use of distance to the geographically nearest mainland misrepresents the complexity of the effects of isolation. We recommend the simultaneous testing of several indices that represent different aspects of isolation, in order to produce more constructive and thorough investigations and avoid imprecise inference

Me, My Girls, and the Ideal Hotel: Segmenting Motivations of the Girlfriend Getaway Market Using Fuzzy C-Medoids for Fuzzy Data.

Segmenting the motivation of travelers using the push and pull framework remains ubiquitous in tourism. This study segments the girlfriend getaway (GGA) market on motivation (push) and accommodation (pull) attributes and identifies relationships between these factors. Using a relatively novel clustering algorithm, the Fuzzy C-Medoids clustering for fuzzy data (FCM-FD), on a sample of 749 women travelers, three segments (Socializers, Enjoyers, and Rejoicers) are uncovered. The results of a multinomial fractional model show relationships between the clusters of motivation and accommodation attributes as well as sociodemographic characteristics. The research highlights the importance of using a gendered perspective in applying well established motivation models such as the push and pull framework. The findings have implications for both destination and accommodation management