Games are widely used as research environments for multiagent reinforcement learning (MARL), but they pose three significant challenges: limited customization, high computational demands, and oversimplification. To address these issues, we introduce the first publicly available map editor for the popular mobile gameHonor of Kingsand design a lightweight environment,Mini Honor of Kings(Mini HoK), for researchers to conduct experiments. Mini HoK is highly efficient, allowing experiments to be run on personal PCs or laptops while still presenting sufficient challenges for existing MARL algorithms. We have tested our environment on common MARL algorithms and demonstrated that these algorithms have yet to surpass the performance of rule based policies, indicating that current MARL methods are not able to solve this environment. This facilitates the dissemination and advancement of MARL methods within the research community. In addition, we hope that more researchers will leverage theHonor of Kingsmap editor to develop innovative and scientifically valuable new maps.

Summary Performance appraisal is a daily, homework, fair, and open appraisal of each hospital, which can mobilize the enthusiasm and creativity of the employees to the greatest extent so that both the company and the employees can achieve development. At present, the ascendant information revolution has become an important factor in promoting the development of the times. The use of advanced information technology to develop advanced information systems to conduct fair and open assessments of the ever‐increasing number of company employees has become the trend of the times. This article makes a historical review of the development and function of the performance appraisal system, and fully analyzes the new features and new functions of the performance appraisal system in the new period, and details the solution. This system develops and uses .NET development platform and SQL Server 2005 database. Using a distributed approach, the system's development costs have reduced, and the system's maintainability and scalability are improved. This paper studies the establishment of a performance‐based distribution model based on diagnostic relevance grouping theory (DRGs) in public hospitals. Based on the DRGs as a theoretical basis, after a long period of historical data collection, a theoretical model was established, repeated regression calculations, and focused evaluations. A performance‐distribution scheme centered on workload has established to reflect the factors such as the labor risk, technical difficulty, and labor cost of the attending doctors in relation to different patient conditions. The formulation and implementation of the new performance plan embodies the input of labor value and conforms to the spirit of the new medical reform.

Stability property is the key index for converter control. A practical stable control scheme is proposed for DC power supply converters. Firstly, the converter system is described as a linear model with two constraints, one is that the input is discontinuous and it is a Finite Control Set (FCS), the other is that the switching frequency is limited. Secondly, a unified control design method satisfied the constraints to guarantee the practical stability and convergence called sampling point equivalence scheme is introduced, which is illustrated as the duty cycle feedback control in form. Then the relationship between the convergent zone and the sampling time is analyzed, which is also the character of practical stability. The DC-DC buck converter is chosen as the plant to show the proposed methods, which are finally validated by both simulation and experiments.

Summary With the continuing incoming connection of distributed generation (DG), in order to guaranty that the DG as a distributed power source provides strong support to the electric system when there is a fault in the electric system, if DG has enough capacity to support part of local loading, allow it to run in island mode and recover to grid‐connected mode after the fault is isolated. Because the formation of island is a dynamic process, how to effectively split to island running mode without affecting the stability of the electric system's running, also, ensure that there is a certain power quality in the island meanwhile keeping and protecting effectively in both island mode and grid‐connected mode. To achieve the aforementioned goals, it needs to develop a plan for comprehensive protection and island division; the plan requires the coordination between the protection and the automatic devices and also needs to take the following into consideration: the capacity of the DG, the location of connection, and the balancing ability of the local loading. This paper will introduce one such comprehensive scheme: It takes consideration of the DG's own characteristics and its ability to support the local loading; it adopts different protection strategy and realizes the fault isolation and island division through the coordination between the protection and the automatic devices. Copyright © 2016 John Wiley & Sons, Ltd.

Entity annotation is a fundamental step for entity relation extraction, information visualization and semantic web creation. Using domain specific ontologies to annotate a dataset for exploring, analyzing and integrating the entities and relations within the corpus is an important step for further study of the data. In this paper, we present an ontology based entity annotation system to annotate entities in neuroscience documents. To improve the annotation performance, we propose an ontology entity expansion method based on web service and ontology structure. We evaluate the proposed entity annotation method on real data obtained from Elsevier's BrainNavigator. The results show that using web service and ontology structure to expand ontology entities can improve the annotation result.

News articles have become an important data source for the general public and researchers. We have developed an interactive visual analytics tool for news exploration (NewsVAT). It includes four main components: preprocessing, analysis, visualization engine and an interface for news exploration. NewsVAT takes news articles as input, and outputs animations reflecting the content of these documents. It provides time series visualization, spatial visualization, co-occurrence network, etc. Rich, flexible and interactive visualization is the prominent feature. In order to test the effectiveness of NewsVAT, a case study was conducted which partly proves the system is effective in news exploration and a helpful aid to research work. Further development includes refining the interactive visualization and improving the accuracy of automatic extraction.

The detection of insulators contamination is difficult in power systems because many factors can influence the pollution. The contamination condition of insulators is usually estimated by detecting the root mean square (r.m.s) of surface leakage current via online-monitoring system. It ignores the influence of environmental factors, such as temperature, humidity, etc. As these factors are fuzzy-characterized, a new method based on Fuzzy Neural Network (FNN) is proposed to improve traditional insulation contamination detection. The renewed structure of FNN is put forward. The evaluation of contamination severity of insulators is achieved through FNN, which are trained by the field samples. The results prove the validity of the method proposed in the paper and can be used to eliminate the insulator from flashover fault and improve the condition-based maintenance (CBM).

In this article, visual concept explorer (VCE), a concept mapping tool, is introduced and its design principles are described. VCE creates dynamic concept maps for the user and facilitates user's visual interaction to concepts and documents. Its central idea is to make implicit knowledge structures explicit. As an example of practical knowledge mapping application, VCE has characteristics of both information visualization and knowledge visualization.

Semantic smoothing, which incorporates synonym and sense information into the language models, is effective and potentially significant to improve retrieval performance. The implemented semantic smoothing models, such as the translation model which statistically maps document terms to query terms, and a number of works that have followed have shown good experimental results. However, these models are unable to incorporate contextual information. Thus, the resulting translation might be mixed and fairly general. To overcome this limitation, we propose a novel context-sensitive semantic smoothing method that decomposes a document or a query into a set of weighted context-sensitive topic signatures and then translate those topic signatures into query terms. In detail, we solve this problem through (1) choosing concept pairs as topic signatures and adopting an ontology-based approach to extract concept pairs; (2) estimating the translation model for each topic signature using the EM algorithm; and (3) expanding document and query models based on topic signature translations. The new smoothing method is evaluated on TREC 2004/05 Genomics Track collections and significant improvements are obtained. The MAP (mean average precision) achieves a 33.6 % maximal gain over the simple language model, as well as a 7.8 % gain over the language model with context-insensitive semantic smoothing.

Automated discovery and extraction of biological knowledge from biomedical web documents has become essential because of the enormous amount of biomedical literature published each year. In this paper we present an ontology-based scalable and portable information extraction system to automatically extract biological knowledge from huge collection of online biomedical web documents. Our method integrates ontology-based semantic tagging, information extraction and data mining together, automatically learns the patterns based on a few user seed tuples, and then extract new tuples from the biomedical web documents based on the discovered patterns. A novel system SPIE (Scalable and Portable Information Extraction) is implemented and tested on the PuBMed to find the chromatin protein-protein interaction and the experimental results indicate our approach is very effective in extracting biological knowledge from huge collection of biomedical web documents.

Using data from the Arts and Humanities Citation Index for 1988-1997, we are attempting to generate co-cited author maps in real time that can serve as interfaces for document retrieval. Our novel approach is to start the maps by entering the name of a single author. Our system obtains a rank-ordered list of the other authors who are most often co-cited with the input name (e.g., the top 50) and then systematically pairs these other authors in turn to obtain their co-citation counts. The resulting matrix can be passed to a mapping program which groups the authors meaningfully to show the structure of the field implied by the input author's name. At present we are experimenting with Pathfinder Networks (PFNETs) as the mapping program, and show a PFNET for 25 authors in hermeneutics, a major field of the humanities. The documents co-citing the mapped authors are candidates for retrieval. We discuss desirable features and design considerations in retrieval interfaces based on PFNETs.

No abstract available.

The focus of this article is to develop a map display for information retrieval. Through an examination of relationships among visual displays, information retrieval, and browsing, advantages of visual displays for information retrieval are characterized as (1) the ability to convey a large amount of information in a limited space, (2) the potential to reveal semantic relationships of terms and documents, and (3) the facilitation of browsing and perceptual inferences on retrieval interfaces. These advantages are further demonstrated through a map display generated by a neural network's self-organizing algorithm. The map display detects complex relationships among given documents, and reveals the relationships through a spatial arrangement of terms abstracted from the documents. The map display also provides interactive tools to allow the user to interact with the underlying information. Examples of the map displays show that such map displays can be used both as an overview tool and an access or exploration tool, and the map displays will likely increase the amount of information that the user is willing to browse.

prototype system that demonstrates this potential is described.

Increasing numbers of researchers and developers are collecting data that trace the processes of human-computer interactions. Although a variety of methods are used to collect such data, all researchers share common problems in representing and analyzing continuous streams of data. A set of methods and tools for graphically representing the search patterns of users interacting with a variety of databases and hypertexts is under development as part of ongoing research in electronic information seeking. The methodology described in this article involves defining state spaces of user options within a system, capturing keystrokes or mouse moves as raw data, coding these data into the state spaces, and analyzing user moves through the state space as evidence of goal-directed information-seeking strategies and patterns. A tool for displaying user moves through a state space has been developed and is described. The tool graphically represents data in a variety of formats, allowing human pattern recognition capabilities to be applied for data analysis. Graphs can be represented for individual searches or for multiple searches done by either a single searcher or by several searchers working on the same search task. © 1991 John Wiley & Sons, Inc.