Multiagent Bidirectionally-Coordinated Nets: Emergence of Human-level Coordination in Learning to Play StarCraft Combat Games

Many artificial intelligence (AI) applications often require multiple intelligent agents to work in a collaborative effort. Efficient learning for intra-agent communication and coordination is an indispensable step towards general AI. In this paper, we take StarCraft combat game as a case study, where the task is to coordinate multiple agents as a team to defeat their enemies. To maintain a scalable yet effective communication protocol, we introduce a Multiagent Bidirectionally-Coordinated Network (BiCNet ['bIknet]) with a vectorised extension of actor-critic formulation. We show that BiCNet can handle different types of combats with arbitrary numbers of AI agents for both sides. Our analysis demonstrates that without any supervisions such as human demonstrations or labelled data, BiCNet could learn various types of advanced coordination strategies that have been commonly used by experienced game players. In our experiments, we evaluate our approach against multiple baselines under different scenarios; it shows state-of-the-art performance, and possesses potential values for large-scale real-world applications.Comment: 10 pages, 10 figures. Previously as title: "Multiagent Bidirectionally-Coordinated Nets for Learning to Play StarCraft Combat Games", Mar 201

Towards A Correct-by-Construction FHE Model

This paper presents a correct-by-construction method of designing an FHE model based on the automated program verifier Dafny. We model FHE operations from the ground up, including fundamentals like GCD, coprimality, Montgomery multiplications, and polynomial operations, etc., and higher level optimizations such as Residue Number System (RNS) and Number Theoretic Transform (NTT). The fully formally verified FHE model serves as a reference design for both software stack development and hardware design, and verification efforts. Open-sourcing our FHE Dafny model with modular arithmetic libraries to GitHub is in progress

RP-HPLC DETERMINATION OF GINSENOSIDES RG1 AND RB1 IN PANAX GINSENG FRUITS

Background: At present, there has been a lot of research at home and abroad on the roots, stems and leaves of Panax Ginseng as well as their extracts, but the fruits of Panax Ginseng have been relatively little studied. Materials and Methods: To establish a method for determination of ginsenosides Rg1 and Rb1 in Panax Ginseng fruits. RP-HPLC method is adopted, column used is a ZOBAX SB-C18 column (4.6 mm × 250 mnl, 5 μm), mobile phase A is water, and B is acetonitrile, gradient elution conditions are: 0~20 min (A:B 20:80), 20~60 min (A:B 20~35: 80~65); and detection wavelength 203 nm. Results: Ginsenosides Rgl and Rb1 have good linear relationships within the ranges of 1.04~10.40 μg and 0.50~5.00 μg, respectively, and r is 0.9998 and 0.9997; reproducibility and recovery of the method are both in line with requirements. Conclusion: The method established is simple, accurate and fast, which is suitable for the simultaneous determination of ginsenosides Rg1 and Rb1 in Panax Ginseng fruits

Application of starch degrading bacteria from tobacco leaves in improving the flavor of flue-cured tobacco

Starch is an essential factor affecting the quality of flue-cured tobacco, and high starch content can affect the sensory quality and safety. Recently, the degradation of macromolecules in tobacco raw materials by using additional microorganisms to improve their intrinsic quality and safety has become a new research hotspot in the tobacco industry. However, the technical maturity and application scale are limited. Our study analyzed the correlation between microbial community composition and volatile components on the surface of tobacco leaves from 14 different grades in Fujian tobacco-producing areas. The PICRUSt software was utilized to predict the function of the microbial community present in tobacco leaves. Furthermore, dominant strains that produced amylase were screened out, and an enzyme solution was prepared to enhance the flue-cured tobacco flavor. Changes in the content of macromolecules and volatile components were determined, and sensory evaluations were conducted to assess the overall quality of the tobacco leaves. The results showed that the dominant bacterial genera on the surface of Fujian tobacco leaves were Variovorax, Sphingomonas, Bacillus, etc. Bacillus was positively correlated with various volatile components, which contributed to the sweet and aromatic flavors of Fujian flue-cured tobacco. The main genetic functions of Fujian flue-cured tobacco surface bacteria were carbohydrate metabolism and amino acid metabolism. After treating flue-cured tobacco with an enzyme preparation prepared by the fermentation of Paenibacillus amylolyticus A17 #, the content of starch, pectin, and cellulose in flue-cured tobacco decreased significantly compared with the control group. Meanwhile, the content of total soluble sugar and reducing sugar was significantly increased, and the volatile aroma components, such as 3-hydroxy--damascone, 2,3-dihydro-3,5-dihydroxy-6-methyl-4 H-Pyran-4-one, ethyl palmitate, ethyl linolenic acid, etc., were significantly increased. The aroma quality and quantity of flue-cured tobacco were enhanced, while impurities were reduced. The smoke characteristics were improved, with increased fineness, concentration, and moderate strength. The taste characteristics were also improved, with reduced irritation and a better aftertaste. In conclusion, Bacillus, as the dominant genus in the abundance of bacterial communities on tobacco surfaces in Fujian, had an essential impact on the flavor of tobacco leaves by participating in carbohydrate metabolism and finally forming the unique flavor style of flue-cured tobacco in Fujian tobacco-producing areas. Paenibacillus amylolyticus A17 #, a target strain with amylase-producing ability, was screened from the surface of Fujian flue-cured tobacco. The enzyme preparation, produced by the fermentation of Paenibacillus amylolyticus A17 #, was utilized to reduce the content of macromolecules, increase the content of water-soluble total sugar and reducing sugar, and produce a variety of crucial volatile aroma components, which had a significant improvement on the quality of tobacco leaves

Eighth International Conference on Intelligent Systems and Knowledge Engineering

"Foundations of Intelligent Systems" presents selected papers from the 2013 International Conference on Intelligent Systems and Knowledge Engineering (ISKE2013). The aim of this conference is to bring together experts from different expertise areas to discuss the state-of-the-art in Intelligent Systems and Knowledge Engineering, and to present new research results and perspectives on future development. The topics in this volume include, but not limited to: Artificial Intelligence Theories, Pattern Recognition, Intelligent System Models, Speech Recognition, Computer Vision, Multi-Agent Systems, Machine Learning, Soft Computing and Fuzzy Systems, Biological Inspired Computation, Game Theory, Cognitive Systems and Information Processing, Computational Intelligence, etc. The proceedings are benefit for both researchers and practitioners who want to utilize intelligent methods in their specific research fields. Dr. Zhenkun Wen is a Professor at the College of Computer and Software Engineering, Shenzhen University, China. Dr. Tianrui Li is a Professor at the School of Information Science and Technology, Southwest Jiaotong University, Xi’an, China."Knowledge Engineering and Management" presents selected papers from the 2013 International Conference on Intelligent Systems and Knowledge Engineering (ISKE2013). The aim of this conference is to bring together experts from different expertise areas to discuss the state-of-the-art in Intelligent Systems and Knowledge Engineering, and to present new research results and perspectives on future development. The topics in this volume include, but not limited to: Knowledge Representation and Modeling, Knowledge Maintenance, Knowledge Elicitation, Knowledge-Based Systems (KBS), Content Management and Knowledge Management Systems, Ontology Engineering, Data Mining and Knowledge Discovery, Knowledge Acquisition, etc. The proceedings are benefit for both researchers and practitioners who want to utilize knowledge engineering methods in their specific research fields. Dr. Zhenkun Wen is a Professor at the College of Computer and Software Engineering, Shenzhen University, China. Dr. Tianrui Li is a Professor at the School of Information Science and Technology, Southwest Jiaotong University, Xi’an, China."Practical Applications of Intelligent Systems" presents selected papers from the 2013 International Conference on Intelligent Systems and Knowledge Engineering (ISKE2013). The aim of this conference is to bring together experts from different expertise areas to discuss the state-of-the-art in Intelligent Systems and Knowledge Engineering, and to present new research results and perspectives on future development. The topics in this volume include, but are not limited to: Intelligent Game, Intelligent Multimedia, Business Intelligence, Intelligent Bioinformatics Systems, Intelligent Healthcare Systems, User Interfaces and Human Computer Interaction, Knowledge-based Software Engineering, Social Issues of Knowledge Engineering, etc. The proceedings are benefit for both researchers and practitioners who want to learn more about the current practice, experience and promising new ideas in the broad area of intelligent systems and knowledge engineering. Dr. Zhenkun Wen is a Professor at the College of Computer and Software Engineering, Shenzhen University, China. Dr. Tianrui Li is a Professor at the School of Information Science and Technology, Southwest Jiaotong University, Xi’an, China

Automatic texture exemplar extraction based on global and local textureness measures

Abstract Texture synthesis is widely used for modeling the appearance of virtual objects. However, traditional texture synthesis techniques emphasize creation of optimal target textures, and pay insufficient attention to choice of suitable input texture exemplars. Currently, obtaining texture exemplars from natural images is a labor intensive task for the artists, requiring careful photography and significant postprocessing. In this paper, we present an automatic texture exemplar extraction method based on global and local textureness measures. To improve the efficiency of dominant texture identification, we first perform Poisson disk sampling to randomly and uniformly crop patches from a natural image. For global textureness assessment, we use a GIST descriptor to distinguish textured patches from non-textured patches, in conjunction with SVM prediction. To identify real texture exemplars consisting solely of the dominant texture, we further measure the local textureness of a patch by extracting and matching the local structure (using binary Gabor pattern (BGP)) and dominant color features (using color histograms) between a patch and its sub-regions. Finally, we obtain optimal texture exemplars by scoring and ranking extracted patches using these global and local textureness measures. We evaluate our method on a variety of images with different kinds of textures. A convincing visual comparison with textures manually selected by an artist and a statistical study demonstrate its effectiveness

Synthesis of Bithiophene-Based D-A1-D-A2 Terpolymers with Different A2 Moieties for Polymer Solar Cells via Direct Arylation

A series of bithiophene (2T)-based D-A1-D-A2 terpolymers with different A2 moieties were prepared via direct arylation reaction. In these terpolymers, pyrrolo[3,4-c]pyrrole-1,4-dione (DPP) was selected as the first electron-accepting (A1) moiety, 2,1,3-benzothiadiazole (BT) or fluorinated benzothiadiazole (FBT) or octyl-thieno[3,4-c]pyrrole-4,6-dione (TPD) or 2,1,3-benzoselendiazole (SeT) was selected as the second electron-accepting (A2) moiety, while bithiophene with hexyl side chain was used as the electron-donating moiety. The UV-vis absorption, electrochemical properties, blend film morphology, and photovoltaic properties were studied to explore the effects of the A2 moiety. It is shown that these terpolymer films exhibit broad absorption (350–1000 nm), full width at half-maximum of more than 265 nm and ordered molecular packing. Varying the A2 moiety could affect the energy levels and blend film morphology leading to different polymer solar cell (PSC) performances of these (2T)-based D-A1-D-A2 terpolymers. As a result, the highest Jsc of 10.70 mA/cm2 is achieved for Polymer 1 (P1) with BT as A2 moiety, while the higher highest occupied molecular orbital (HOMO) level limits the open circuit voltage (Voc) and leads to a power conversion efficiency (PCE) of 3.46%

Deep Style Transfer for Line Drawings

Line drawings are frequently used to illustrate ideas and concepts in digital documents and presentations. To compose a line drawing, it is common for users to retrieve multiple line drawings from the Internet and combine them as one image. However, different line drawings may have different line styles and are visually inconsistent when put together. In order that the line drawings can have consistent looks, in this paper, we make the first attempt to perform style transfer for line drawings. The key of our design lies in the fact that centerline plays a very important role in preserving line topology and extracting style features. With this finding, we propose to formulate the style transfer problem as a centerline stylization problem and solve it via a novel style-guided image-to-image translation network. Results and statistics show that our method significantly outperforms the existing methods both visually and quantitatively