An Architectural Approach to Ensuring Consistency in Hierarchical Execution

Hierarchical task decomposition is a method used in many agent systems to organize agent knowledge. This work shows how the combination of a hierarchy and persistent assertions of knowledge can lead to difficulty in maintaining logical consistency in asserted knowledge. We explore the problematic consequences of persistent assumptions in the reasoning process and introduce novel potential solutions. Having implemented one of the possible solutions, Dynamic Hierarchical Justification, its effectiveness is demonstrated with an empirical analysis

Estimating Effects and Making Predictions from Genome-Wide Marker Data

In genome-wide association studies (GWAS), hundreds of thousands of genetic markers (SNPs) are tested for association with a trait or phenotype. Reported effects tend to be larger in magnitude than the true effects of these markers, the so-called ``winner's curse.'' We argue that the classical definition of unbiasedness is not useful in this context and propose to use a different definition of unbiasedness that is a property of the estimator we advocate. We suggest an integrated approach to the estimation of the SNP effects and to the prediction of trait values, treating SNP effects as random instead of fixed effects. Statistical methods traditionally used in the prediction of trait values in the genetics of livestock, which predates the availability of SNP data, can be applied to analysis of GWAS, giving better estimates of the SNP effects and predictions of phenotypic and genetic values in individuals.Comment: Published in at http://dx.doi.org/10.1214/09-STS306 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Multi-locus models of genetic risk of disease

Background: Evidence for genetic contribution to complex diseases is described by recurrence risks to relatives of diseased individuals. Genome-wide association studies allow a description of the genetics of the same diseases in terms of risk loci, their effects and allele frequencies. To reconcile the two descriptions requires a model of how risks from individual loci combine to determine an individual's overall risk

Prediction of individual genetic risk to disease from genome-wide association studies

Empirical studies suggest that the effect sizes of individual causal risk alleles underlying complex genetic diseases are small, with most genotype relative risks in the range of 1.1-2.0. Although the increased risk of disease for a carrier is small for any single locus, knowledge of multiple-risk alleles throughout the genome could allow the identification of individuals that are at high risk. In this study, we investigate the number and effect size of risk loci that underlie complex disease constrained by the disease parameters of prevalence and heritability. Then we quantify the value of prediction of genetic risk to disease using a range of realistic combinations of the number, size, and distribution of risk effects that underlie complex diseases. We propose an approach to assess the genetic risk of a disease in healthy individuals, based on dense genome-wide SNP panels. We test this approach using simulation. When the number of loci contributing to the disease is >50, a large case-control study is needed to identify a set of risk loci for use in predicting the disease risk of healthy people not included in the case-control study. For diseases controlled by 1000 loci of mean relative risk of only 1.04, a case-control study with 10,000 cases and controls can lead to selection of ∼75 loci that explain >50% of the genetic variance. The 5% of people with the highest predicted risk are three to seven times more likely to suffer the disease than the population average, depending on heritability and disease prevalence. Whether an individual with known genetic risk develops the disease depends on known and unknown environmental factors

Improving Language Model Prompting in Support of Semi-autonomous Task Learning

Language models (LLMs) offer potential as a source of knowledge for agents that need to acquire new task competencies within a performance environment. We describe efforts toward a novel agent capability that can construct cues (or "prompts") that result in useful LLM responses for an agent learning a new task. Importantly, responses must not only be "reasonable" (a measure used commonly in research on knowledge extraction from LLMs) but also specific to the agent's task context and in a form that the agent can interpret given its native language capacities. We summarize a series of empirical investigations of prompting strategies and evaluate responses against the goals of targeted and actionable responses for task learning. Our results demonstrate that actionable task knowledge can be obtained from LLMs in support of online agent task learning.Comment: Submitted to ACS 202

Improving Knowledge Extraction from LLMs for Task Learning through Agent Analysis

Large language models (LLMs) offer significant promise as a knowledge source for task learning. Prompt engineering has been shown to be effective for eliciting knowledge from an LLM, but alone it is insufficient for acquiring relevant, situationally grounded knowledge for an embodied agent learning novel tasks. We describe a cognitive-agent approach, STARS, that extends and complements prompt engineering, mitigating its limitations and thus enabling an agent to acquire new task knowledge matched to its native language capabilities, embodiment, environment, and user preferences. The STARS approach is to increase the response space of LLMs and deploy general strategies, embedded within the autonomous agent, to evaluate, repair, and select among candidate responses produced by the LLM. We describe the approach and experiments that show how an agent, by retrieving and evaluating a breadth of responses from the LLM, can achieve 77-94% task completion in one-shot learning without user oversight. The approach achieves 100% task completion when human oversight (such as an indication of preference) is provided. Further, the type of oversight largely shifts from explicit, natural language instruction to simple confirmation/discomfirmation of high-quality responses that have been vetted by the agent before presentation to a user.Comment: 7 pages, 8 figures, 3 tables, bibliography, appendix (34 pages total). Accepted to AAAI 202

Emergence of Fermi pockets in an excitonic CDW melted novel superconductor

A superconducting (SC) state (Tc ~ 4.2K) has very recently been observed upon successful doping of the CDW ordered triangular lattice TiSe$_2$, with copper. Using high resolution photoemission spectroscopy we identify, for the first time, the momentum space locations of the doped electrons that form the Fermi sea of the parent superconductor. With doping, we find that the kinematic nesting volume increases whereas the coherence of the CDW order sharply drops. In the superconducting doping, we observe the emergence of a large density of states in the form of a narrow electron pocket near the \textit{L}-point of the Brillouin Zone with \textit{d}-like character. The \textit{k}-space electron distributions highlight the unconventional interplay of CDW to SC cross-over achieved through non-magnetic copper doping.Comment: 4+ pages, 5 figures; Accepted for publication in Phys. Rev. Lett. (2007

The rodent research animal holding facility as a barrier to environmental contamination

The rodent Research Animal Holding Facility (RAHF), developed by NASA Ames Research Center (ARC) to separately house rodents in a Spacelab, was verified as a barrier to environmental contaminants during a 12-day biocompatibility test. Environmental contaminants considered were solid particulates, microorganisms, ammonia, and typical animal odors. The 12-day test conducted in August 1988 was designed to verify that the rodent RAHF system would adequately support and maintain animal specimens during normal system operations. Additional objectives of this test were to demonstrate that: (1) the system would capture typical particulate debris produced by the animal; (2) microorganisms would be contained; and (3) the passage of animal odors was adequately controlled. In addition, the amount of carbon dioxide exhausted by the RAHF system was to be quantified. Of primary importance during the test was the demonstration that the RAHF would contain particles greater than 150 micrometers. This was verified after analyzing collection plates placed under exhaust air ducts and rodent cages during cage maintenance operations, e.g., waste tray and feeder changeouts. Microbiological testing identified no additional organisms in the test environment that could be traced to the RAHF. Odor containment was demonstrated to be less than barely detectable. Ammonia could not be detected in the exhaust air from the RAHF system. Carbon dioxide levels were verified to be less than 0.35 percent

Membrane Cholesterol Regulates Smooth Muscle Phasic Contraction

The regulation of contractile activity in smooth muscle cells involves rapid discrimination and processing of a multitude of simultaneous signals impinging on the membrane before an integrated functional response can be generated. The sarcolemma of smooth muscle cells is segregated into caveolar regions-largely identical with cholesterol-rich membrane rafts—and actin-attachment sites, localized in non-raft, glycerophospholipid regions. Here we demonstrate that selective extraction of cholesterol abolishes membrane segregation and disassembles caveolae. Simultaneous measurements of force and [Ca2+]i in rat ureters demonstrated that extraction of cholesterol resulted in inhibition of both force and intracellular Ca2+ signals. Considering the major structural reorganization of cholesterol-depleted sarcolemma, it is intriguing to note that decreased levels of membrane cholesterol are accompanied by a highly specific inhibition of phasic, but not tonic contractions. This implies that signalling cascades that ultimately lead to either phasic or tonic response may be spatially segregated in the plane of the sarcolemma. Replenishment of cholesterol restores normal contractile behavior. In addition, the tissue function is re-established by inhibiting the large-conductance K+-channel. Sucrose gradient ultracentrifugation in combination with Western blotting analysis demonstrates that its α-subunit is associated with detergent-resistant membranes, suggesting that the channel might be localized within the membrane rafts in vivo. These findings are important in understanding the complex signalling pathways in smooth muscle and conditions such as premature labor and hypertensio