637 research outputs found

    MiniZero: Comparative Analysis of AlphaZero and MuZero on Go, Othello, and Atari Games

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    This paper presents MiniZero, a zero-knowledge learning framework that supports four state-of-the-art algorithms, including AlphaZero, MuZero, Gumbel AlphaZero, and Gumbel MuZero. While these algorithms have demonstrated super-human performance in many games, it remains unclear which among them is most suitable or efficient for specific tasks. Through MiniZero, we systematically evaluate the performance of each algorithm in two board games, 9x9 Go and 8x8 Othello, as well as 57 Atari games. For two board games, using more simulations generally results in higher performance. However, the choice of AlphaZero and MuZero may differ based on game properties. For Atari games, both MuZero and Gumbel MuZero are worth considering. Since each game has unique characteristics, different algorithms and simulations yield varying results. In addition, we introduce an approach, called progressive simulation, which progressively increases the simulation budget during training to allocate computation more efficiently. Our empirical results demonstrate that progressive simulation achieves significantly superior performance in two board games. By making our framework and trained models publicly available, this paper contributes a benchmark for future research on zero-knowledge learning algorithms, assisting researchers in algorithm selection and comparison against these zero-knowledge learning baselines. Our code and data are available at https://rlg.iis.sinica.edu.tw/papers/minizero.Comment: Submitted to IEEE Transactions on Games, under revie

    Ferroelectric Control of the Conduction at the LaAlO 3 /SrTiO 3 Hetero-interface

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    Abstract The LaAlO 3 /SrTiO 3 (LAO/STO) interface serves as a model system in which a highly mobile quasi-twodimensional electron gas (2DEG) forms between two band insulator

    Efficacy of the visual cognitive assessment test for mild cognitive impairment/mild dementia diagnosis: a meta-analysis

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    BackgroundMild cognitive impairment (MCI) is an intermediate stage between normal ageing and dementia. The early identification of MCI is important for timely intervention. The visual cognitive assessment test (VCAT) is a brief language-neutral screening tool for detecting MCI/mild dementia. This meta-analysis evaluated the diagnostic efficacy of the VCAT for MCI/mild dementia.MethodsMedline, Embase, Google Scholar, and Cochrane Library were searched from their inception until August 2023 to identify studies using VCAT to diagnose MCI/mild dementia. The primary outcome was to assess the diagnostic accuracy of the VCAT for detecting MCI/mild dementia through area under the receiver operating characteristic curve (AU-ROC) analysis. The secondary outcome was to explore the correlation between VCAT scores and MCI/mild dementia presence by comparing scores among patients with and without MCI/mild dementia. Pooled sensitivity, specificity, and area under the curve (AUC) were calculated.ResultsFive studies with 1,446 older adults (mean age 64–68.3 years) were included. The percentage of participants with MCI/mild dementia versus controls ranged from 16.5% to 87% across studies. All studies were conducted in Asian populations, mostly Chinese, in Singapore and Malaysia. The pooled sensitivity was 80% [95% confidence interval (CI) 68%–88%] and the specificity was 75% (95% CI 68%–80%). The AU-ROCC was 0.77 (95% CI 0.73–0.81). Patients with MCI/mild dementia had lower VCAT scores than the controls (mean difference −6.85 points, p < 0.00001).ConclusionVCAT demonstrated acceptable diagnostic accuracy in distinguishing MCI/mild dementia in cognitively normal older adults. As a language-neutral and culturally unbiased tool, the VCAT shows promise in detecting MCI/mild dementia. Further studies in non-Asian populations are required.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier: CRD42023453453

    Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

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    Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

    Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

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    A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

    Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

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    Measurement of nuclear modification factors of gamma(1S)), gamma(2S), and gamma(3S) mesons in PbPb collisions at root s(NN)=5.02 TeV

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    The cross sections for ϒ(1S), ϒ(2S), and ϒ(3S) production in lead-lead (PbPb) and proton-proton (pp) collisions at √sNN = 5.02 TeV have been measured using the CMS detector at the LHC. The nuclear modification factors, RAA, derived from the PbPb-to-pp ratio of yields for each state, are studied as functions of meson rapidity and transverse momentum, as well as PbPb collision centrality. The yields of all three states are found to be significantly suppressed, and compatible with a sequential ordering of the suppression, RAA(ϒ(1S)) > RAA(ϒ(2S)) > RAA(ϒ(3S)). The suppression of ϒ(1S) is larger than that seen at √sNN = 2.76 TeV, although the two are compatible within uncertainties. The upper limit on the RAA of ϒ(3S) integrated over pT, rapidity and centrality is 0.096 at 95% confidence level, which is the strongest suppression observed for a quarkonium state in heavy ion collisions to date. © 2019 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3.Peer reviewe
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