An information-based approach to integrating empirical and explanation-based learning

We describe a new approach to integrating explanation-based and empirical learning methods for learning relational concepts. The approach uses an information-based heuristic to evaluate components of a hypothesis that are proposed either by explanation-based or empirical methods. Providing domain knowledge to the integrated system can decrease the amount of search required during learning and increase the accuracy of learned concepts, even when the domain knowledge is incorrect and incomplete and there is noise in the training data

Retrofitting O'Raifeartaigh Models with Dynamical Scales

We provide a method for obtaining simple models of supersymmetry breaking, with all small mass scales generated dynamically, and illustrate it with explicit examples. We start from models of perturbative supersymmetry breaking, such as O'Raifeartaigh and Fayet models, that would respect an $R$ symmetry if their small input parameters transformed as the superpotential does. By coupling the system to a pure supersymmetric Yang-Mills theory (or a more general supersymmetric gauge theory with dynamically small vacuum expectation values), these parameters are replaced by powers of its dynamical scale in a way that is naturally enforced by the symmetry. We show that supersymmetry breaking in these models may be straightforwardly mediated to the supersymmetric Standard Model, obtain complete models of direct gauge mediation, and comment on related model building strategies that arise in this simple framework.Comment: 15 pages, harvmac bi

Washington Pension System Review

The purpose of this study is to analyze the incidence of Total Permanent Disability (TPD)pensions in Washington State's workers' compensation program. Concerns exist at both thelegislature and in the Department of Labor and Industries as there appears to have been a sharp upturn in the number of pensions awarded since late in the 1990s. This report examines the factors that may be causally related to any upsurge in such awards. Our task is to evaluate pension incidence for both the state fund and the self-insured populations, with a view towards identifying causes of the trend in both sectors, although we concentrate more on the state fund Cclaims due to data limitations

Implications of Information Theory for Computational Modeling of Schizophrenia

Information theory provides a formal framework within which information processing and its disorders can be described. However, information theory has rarely been applied to modeling aspects of the cognitive neuroscience of schizophrenia. The goal of this article is to highlight the benefits of an approach based on information theory, including its recent extensions, for understanding several disrupted neural goal functions as well as related cognitive and symptomatic phenomena in schizophrenia. We begin by demonstrating that foundational concepts from information theory—such as Shannon information, entropy, data compression, block coding, and strategies to increase the signal-to-noise ratio—can be used to provide novel understandings of cognitive impairments in schizophrenia and metrics to evaluate their integrity. We then describe more recent developments in information theory, including the concepts of infomax, coherent infomax, and coding with synergy, to demonstrate how these can be used to develop computational models of schizophrenia-related failures in the tuning of sensory neurons, gain control, perceptual organization, thought organization, selective attention, context processing, predictive coding, and cognitive control. Throughout, we demonstrate how disordered mechanisms may explain both perceptual/cognitive changes and symptom emergence in schizophrenia. Finally, we demonstrate that there is consistency between some information-theoretic concepts and recent discoveries in neurobiology, especially involving the existence of distinct sites for the accumulation of driving input and contextual information prior to their interaction. This convergence can be used to guide future theory, experiment, and treatment development

Deixis and Deducibility in a Wasco-Wishram Passive of Evidence

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Kiksht “Impersonals” as Anaphors and the Predictiveness of Grammatical-Categorial Universals

Proceedings of the Twenty-First Annual Meeting of the Berkeley Linguistics Society: General Session and Parasession on Historical Issues in Sociolinguistics/Social Issues in Historical Linguistics (1995

Classifiers, Verb Classifiers, and Verbal Categories

Proceedings of the Twelfth Annual Meeting of the Berkeley Linguistics Society (1986), pp. 497-51