Generating Interpretable Fuzzy Controllers using Particle Swarm Optimization and Genetic Programming

Autonomously training interpretable control strategies, called policies, using pre-existing plant trajectory data is of great interest in industrial applications. Fuzzy controllers have been used in industry for decades as interpretable and efficient system controllers. In this study, we introduce a fuzzy genetic programming (GP) approach called fuzzy GP reinforcement learning (FGPRL) that can select the relevant state features, determine the size of the required fuzzy rule set, and automatically adjust all the controller parameters simultaneously. Each GP individual's fitness is computed using model-based batch reinforcement learning (RL), which first trains a model using available system samples and subsequently performs Monte Carlo rollouts to predict each policy candidate's performance. We compare FGPRL to an extended version of a related method called fuzzy particle swarm reinforcement learning (FPSRL), which uses swarm intelligence to tune the fuzzy policy parameters. Experiments using an industrial benchmark show that FGPRL is able to autonomously learn interpretable fuzzy policies with high control performance.Comment: Accepted at Genetic and Evolutionary Computation Conference 2018 (GECCO '18

Patent Institutions: Shifting Interactions Between Legal Actors

This contribution to the Research Handbook on Economics of Intellectual Property Rights (Vol. 1 Theory) addresses interactions between the principal legal institutions of the U.S. patent system. It considers legal, strategic, and normative perspectives on these interactions as they have evolved over the last 35 years. Early centralization of power by the U.S. Court of Appeals for the Federal Circuit, newly created in 1982, established a regime dominated by the appellate court\u27s bright-line rules. More recently, aggressive Supreme Court and Congressional intervention have respectively reinvigorated patent law standards and led to significant devolution of power to inferior tribunals, including newly created tribunals like the USPTO\u27s Patent Trial and Appeals Board. This new era in institutional interaction creates a host of fresh empirical and normative research questions for scholars. The contribution concludes by outlining a research agenda

The Crisis of Finance-Dominated Capitalism in the Euro Area, Deficiencies in the Economic Policy Architecture, and Deflationary Stagnation Policies

* For a more detailed elaboration on the macroeconomic theory of finance-dominated capitalism, see the respective chapters in my book The Macroeconomics of Finance-dominated Capitalism – and Its Crisis (Hein 2012a). The present paper is based on this theory, and it extends and updates the analysis of the euro crisis I have presented in Hein (2012b). I would like to thank Achim Truger for his helpful comments and Matthias Mundt for his valuable research assistance. The Levy Economics Institute Working Paper Collection presents research in progress by Levy Institute scholars and conference participants. The purpose of the series is to disseminate ideas to and elicit comments from academics and professionals. Levy Economics Institute of Bard College, founded in 1986, is a nonprofit, nonpartisan, independently funded research organization devoted to public service. Through scholarship and economic research it generates viable, effective public policy responses to important economic problems that profoundly affect the quality of life in the United States and abroad

Superconducting and Normal State Properties of Heavily Hole-Doped Diamond

We report measurements of the specific heat, Hall effect, upper critical field and resistivity on bulk, B-doped diamond prepared by reacting amorphous B and graphite under high-pressure/high-temperature conditions. These experiments establish unambiguous evidence for bulk superconductivity and provide a consistent set of materials parameters that favor a conventional, weak coupling electron-phonon interpretation of the superconducting mechanism at high hole doping.Comment: 10 pages, 3 figure

The Effect of Temperature, Relative Humidity, and Virus Infection Status on off-host Survival of the Wheat Curl Mite (Acari: Eriophyidae)

The wheat curl mite, Aceria tosichella Keifer, is an eriophyid pest of wheat, although its primary economic impact on wheat is due to the transmission of Wheat streak mosaic (WSMV), Wheat mosaic (also known as High Plains virus), and Triticum mosaic (TriMV) viruses. These viruses cause significant annual losses in winter wheat production throughout the western Great Plains. Temperature and humidity are factors that often influence arthropod survival, especially during dispersal from their hosts, yet the impact of these two factors on off-host survival has not been documented for wheat curl mite. Pathogen- infected host plants often influence the biology and behavior of vectors, yet it is not known if virus-infected wheat affects off-host survival of wheat curl mite. The objectives of this study were to 1) determine if temperature, relative humidity, and mite genotype impact off-host survival of wheat curl mite and 2) determine the effect of WSMV- and TriMV-infected host plants on off-host survival of wheat curl mite. Temperature and relative humidity significantly affected off-host survival of wheat curl mite. Length of survival decreased with increasing temperature (106.2 h at 10°C and 17.0 h at 30°C) and decreasing relative humidity (78.1 h at 95 and 21.3 h at 2%). Mites from TriMV-infected host plants had ~20% reduction in survival at 20°C compared with those from WSMV-infected plants. The duration of off-host survival of wheat curl mite is influenced by environmental conditions. Management strategies that target a break in host presence will greatly reduce mite densities and virus spread and need to account for these limits

Uncertainty-Aware Organ Classification for Surgical Data Science Applications in Laparoscopy

Objective: Surgical data science is evolving into a research field that aims to observe everything occurring within and around the treatment process to provide situation-aware data-driven assistance. In the context of endoscopic video analysis, the accurate classification of organs in the field of view of the camera proffers a technical challenge. Herein, we propose a new approach to anatomical structure classification and image tagging that features an intrinsic measure of confidence to estimate its own performance with high reliability and which can be applied to both RGB and multispectral imaging (MI) data. Methods: Organ recognition is performed using a superpixel classification strategy based on textural and reflectance information. Classification confidence is estimated by analyzing the dispersion of class probabilities. Assessment of the proposed technology is performed through a comprehensive in vivo study with seven pigs. Results: When applied to image tagging, mean accuracy in our experiments increased from 65% (RGB) and 80% (MI) to 90% (RGB) and 96% (MI) with the confidence measure. Conclusion: Results showed that the confidence measure had a significant influence on the classification accuracy, and MI data are better suited for anatomical structure labeling than RGB data. Significance: This work significantly enhances the state of art in automatic labeling of endoscopic videos by introducing the use of the confidence metric, and by being the first study to use MI data for in vivo laparoscopic tissue classification. The data of our experiments will be released as the first in vivo MI dataset upon publication of this paper.Comment: 7 pages, 6 images, 2 table

Overcoming early career barriers to interdisciplinary climate change research

Climate-change impacts are among the most serious and complex challenges facing society, affecting both natural and social systems. Addressing these requires a new paradigm of interdisciplinary collaboration which incorporates tools, techniques, and insights from across the social, natural, and engineering sciences. Yet, a wide range of intrinsic and extrinsic hurdles need to be overcome to conduct successful, integrated interdisciplinary research. The results of a bibliometric analysis and survey of early to mid-career scientists from 56 countries who were involved with the interdisciplinary DISsertations initiative for the advancement of Climate Change ReSearch (DISCCRS) emphasize the particular challenges faced by early career researchers. Survey respondents perceive conflict between the need for interdisciplinary climate-change research and its potential detriment to career advancement. However, participation in interventions for early career scientists, such as networking and training symposia, had both perceived and measurable impacts on the likelihood of engagement in climate-centric interdisciplinary research. Respondents also ranked alternative mechanisms for encouraging incorporation of interdisciplinary science at early career stages, prioritizing funding of interdisciplinary seed grants, fellowships, and junior faculty networks, interdisciplinary teamwork and communication training, and interdepartmental symposia. To this we add the suggestion that interdisciplinarity be incorporated into tenure and promotion evaluations through the use of exploratory science mapping tools. Despite the need to foster interdisciplinary research and the availability of multiple prospective solutions, there remain expansive structural challenges to its promotion and recognition which, unless collectively addressed, will continue to hinder its potential growth and application to climate-change science