Score-Based Equilibrium Learning in Multi-Player Finite Games with Imperfect Information

Real-world games, which concern imperfect information, multiple players, and simultaneous moves, are less frequently discussed in the existing literature of game theory. While reinforcement learning (RL) provides a general framework to extend the game theoretical algorithms, the assumptions that guarantee their convergence towards Nash equilibria may no longer hold in real-world games. Starting from the definition of the Nash distribution, we construct a continuous-time dynamic named imperfect-information exponential-decay score-based learning (IESL) to find approximate Nash equilibria in games with the above-mentioned features. Theoretical analysis demonstrates that IESL yields equilibrium-approaching policies in imperfect information simultaneous games with the basic assumption of concavity. Experimental results show that IESL manages to find approximate Nash equilibria in four canonical poker scenarios and significantly outperforms three other representative algorithms in 3-player Leduc poker, manifesting its equilibrium-finding ability even in practical sequential games. Furthermore, related to the concept of game hypomonotonicity, a trade-off between the convergence of the IESL dynamic and the ultimate NashConv of the convergent policies is observed from the perspectives of both theory and experiment

Reionizing islands with inhomogeneous recombinations

Observations are beginning to constrain the history of the epoch of reionization (EoR). Modeling the reionization process is indispensable to interpret the observations, to infer the properties of ionizing sources, and to probe the various astrophysical processes from the observational data. Here we present an improved version of the semi-numerical simulation islandFAST, by incorporating inhomogeneous recombinations and a corresponding inhomogeneous ionizing background, and simulate the reionization process of neutral islands during the late EoR. We find that the islands are more fragmented in models with inhomogeneous recombinations than the case with a homogeneous recombination number. In order to investigate the effects of basic assumptions in the reionization modeling, we compare the results from islandFAST with those from 21cmFAST for the same assumptions on the ionizing photon sources and sinks, to find how the morphology of the ionization field and the reionization history depend on the different treatments of these two models. Such systematic bias should be noted when interpreting the upcoming observations.Comment: 19 pages, 10 figures. Accepted for publication in Research in Astronomy and Astrophysic

3DG-STFM: 3D Geometric Guided Student-Teacher Feature Matching

We tackle the essential task of finding dense visual correspondences between a pair of images. This is a challenging problem due to various factors such as poor texture, repetitive patterns, illumination variation, and motion blur in practical scenarios. In contrast to methods that use dense correspondence ground-truths as direct supervision for local feature matching training, we train 3DG-STFM: a multi-modal matching model (Teacher) to enforce the depth consistency under 3D dense correspondence supervision and transfer the knowledge to 2D unimodal matching model (Student). Both teacher and student models consist of two transformer-based matching modules that obtain dense correspondences in a coarse-to-fine manner. The teacher model guides the student model to learn RGB-induced depth information for the matching purpose on both coarse and fine branches. We also evaluate 3DG-STFM on a model compression task. To the best of our knowledge, 3DG-STFM is the first student-teacher learning method for the local feature matching task. The experiments show that our method outperforms state-of-the-art methods on indoor and outdoor camera pose estimations, and homography estimation problems. Code is available at: https://github.com/Ryan-prime/3DG-STFM

Bio-inspired plasmonic nanoarchitectured hybrid system towards enhanced far red-to-near infrared solar photocatalysis

Solar conversion to fuels or to electricity in semiconductors using far red-to-near infrared (NIR) light, which accounts for about 40% of solar energy, is highly significant. One main challenge is the development of novel strategies for activity promotion and new basic mechanisms for NIR response. Mother Nature has evolved to smartly capture far red-to-NIR light via their intelligent systems due to unique micro/nanoarchitectures, thus motivating us for biomimetic design. Here we report the first demonstration of a new strategy, based on adopting nature’s far red-to-NIR responsive architectures for an efficient bio-inspired photocatalytic system. The system is constructed by controlled assembly of light-harvesting plasmonic nanoantennas onto a typical photocatalytic unit with butterfly wings’ 3D micro/nanoarchitectures. Experiments and finite-difference time-domain (FDTD) simulations demonstrate the structural effects on obvious far red-to-NIR photocatalysis enhancement, which originates from (1) Enhancing far red-to-NIR (700~1200 nm) harvesting, up to 25%. (2) Enhancing electric-field amplitude of localized surface plasmon (LSPs) to more than 3.5 times than that of the non-structured one, which promotes the rate of electron-hole pair formation, thus substantially reinforcing photocatalysis. This proof-of-concept study provides a new methodology for NIR photocatalysis and would potentially guide future conceptually new NIR responsive system designs

An Effective Sharding Consensus Algorithm for Blockchain Systems

Sharding is the widely used approach to the trilemma of simultaneously achieving decentralization, security, and scalability in traditional blockchain systems. However, existing schemes generally involve problems such as uneven shard arithmetic power and insecure cross-shard transaction processing. In this study, we used the Practical Byzantine Fault Tolerance (PBFT) as the intra-shard consensus and, here, we propose a new sharding consensus mechanism. Firstly, we combined a jump consistent hash algorithm with signature Anchorhash to minimize the mapping of the node assignment. Then, we improved the process of the cross-shard transaction and used the activity of nodes participating in intra-shard transactions as the criterion for the shard reconfiguration, which ensured the security of the blockchain system. Meanwhile, we analyzed the motivation mechanism from two perspectives. Finally, through theoretical analysis and related experiments, we not only verified that the algorithm can ensure the security of the entire system, but also further clarified the necessary conditions to ensure the effectiveness of the shards and the system on the original basis

An Overview of Systematic Reviews of Using Chinese Medicine to Treat Polycystic Ovary Syndrome

Objective. This review sought to evaluate the strength and validity of the existing evidence for the use of Chinese medicine for the treatment of polycystic ovary syndrome (PCOS). Methods. We retrieved systematic evaluations and meta-analyses of randomized controlled trials (RCTs) evaluating Chinese herbal interventions in polycystic ovaries, including the use of decoctions or Chinese patent medicines. The quality of these systematic evaluations was assessed using AMSTAR2 tools, and ovulation rate, pregnancy rate, effective rate, serum hormones (testosterone, luteinizing hormone, and follicle-stimulating hormone), and adverse reactions were recorded. Finally, the reliability of each result was evaluated according to the GRADE system. Data Sources. PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang Data, CQVIP, and SINOMED databases were searched up to January 1, 2021. Outcomes. A total of 18 publications were included, all of which showed that PCOS symptoms were improved with Chinese medicine compared with control groups. However, most of the evaluations did not have good research designs and had issues with the analysis of their results. The reliability of most outcome measures was rated low or very low, and it is presumed that the reliability of the results was low due to the poor quality of the RCTs. Conclusions. At present, there is insufficient evidence to suggest that improved efficacy is achieved by the combined use of Chinese and Western medicine compared with Western medicine alone in treating PCOS. Therefore, it is recommended that multicenter, large-sample RCTs adopting standard designs and rigorous methods be carried out in the future while introducing standardized assessment plans for the systematic review of clinical trials so as to improve the quality of the resulting clinical evidence

Discrete particle simulation of particulate systems: a review of major applications and findings

Understanding and modelling the dynamic behaviour of particulate systems has been a major research focus worldwide for many years. Discrete particle simulation plays an important role in this area. This technique can provide dynamic information, such as the trajectories of and transient forces acting on in- dividual particles, which is difficult to obtain by the conventional experimental techniques. Consequently, it has been increasingly used by various investigators for different particulate processes. In spite of the large bulk volume, little effort has been made to comprehensively review and summarize the progress made in the past. To overcome this gap, we have recently completed a review of the major work in this area in two separate parts. The first part has been published [Zhu, H.P., Zhou, Z.Y., Yang, R.Y., Yu, A.B., 2007. Discrete particle simulation of particulate systems: theoretical developments. Chemical Engineering Science 62, 3378–3392.], which reviews the major theoretical developments. This paper is the second one, aiming to provide a summary of the studies based on discrete particle simulation in the past two decades or so. The studies are categorized into three subject areas: particle packing, particle flow, and particle–fluid flow. The major findings are discussed, with emphasis on the microdynamics including packing/flow structure and particle–particle, particle–fluid and particle–wall interaction forces. It is con- cluded that discrete particle simulation is an effective method for particle scale research of particulate matter. The needs for future research are also discussed