A framework for analyzing playability requirements based on game reviews

Requirements Engineering is an important phase in software development. Game development also requires Requirement Engineering, due to the frequently changes of requirements during the process of the game development [Kasurinen et al., 2014]. However, only a few studies have linked the game development and Requirements Engineering together. Research in related fields is inadequate and needs to be studied in depth Playability is a crucial concept for the game study. For a player, playability is highly related to the player experience, especially the experience of enjoyment. For a video game, the quality of game components affects the degree of playability. Playability is often used for evaluating the video game, but studies focus on playability are insufficient [Korhonen, 2016, p21]. Moreover, few researchers study playability from the perspective of Requirement Engineering. This thesis supposes playability as a kind of non-functional requirements that is important for the game development. The aim of the thesis is to help game designers or testers understand and analyse playability requirements systematically. The thesis work includes two parts, literature review and data analysis. Literature referred to playability, game components and game enjoyment was mainly studied. Based on the literature review, 41 game reviews from GameSpot were collected and analysed by grounded theory. As a result, Playability Framework was developed for understanding and analyzing playability requirements. There are three categories of playability, including Gameplay, Representation and Story. This thesis focuses on Gameplay, since most of data belongs to Gameplay. Furthermore, four elements of Gameplay were concluded, including Goals, Gameworld, Avatar and Player. Through analysing the relationships between the four elements, Gameplay are categorized into three groups, Achievements of goals, Game interaction and Game control. In addition, five attributes that highly affect the quality of gameplay were found during the data analysis, they are Variety, Meaningfulness, Fairness, Pace and Intuitiveness. Based on the framework, the steps of analysing player requirements and the form of playability requirements were also proposed. The result of the thesis can help game designers and testers transfer playability issues into playability requirements, so that the issues can be analyzed and tracked systematically

Efficient Deep Reinforcement Learning via Adaptive Policy Transfer

Transfer Learning (TL) has shown great potential to accelerate Reinforcement Learning (RL) by leveraging prior knowledge from past learned policies of relevant tasks. Existing transfer approaches either explicitly computes the similarity between tasks or select appropriate source policies to provide guided explorations for the target task. However, how to directly optimize the target policy by alternatively utilizing knowledge from appropriate source policies without explicitly measuring the similarity is currently missing. In this paper, we propose a novel Policy Transfer Framework (PTF) to accelerate RL by taking advantage of this idea. Our framework learns when and which source policy is the best to reuse for the target policy and when to terminate it by modeling multi-policy transfer as the option learning problem. PTF can be easily combined with existing deep RL approaches. Experimental results show it significantly accelerates the learning process and surpasses state-of-the-art policy transfer methods in terms of learning efficiency and final performance in both discrete and continuous action spaces.Comment: Accepted by IJCAI'202

Noticiário

In an attempt to achieve the selective oxidation of NOx, a hybrid catalyst of single-atom-anchored metal organic frameworks (MOF, NH2-UiO-66) and MnO2 was constructed and used in the plasma catalytic process. Isolated Ru sites were successfully implanted into the structure of the MOF by simply stirring the mixed liquor containing both MOF and RuCl3, facilitating plasma discharge, NO/NO2 adsorption, and formation of âOH radicals. A special oxo-bridged Zr4+-O-Ru3+ was constructed to accelerate electron transfer and continuous proceeding of the reaction. Directional migration of generated electrons from MOF to Ru sites was witnessed when MOF was activated by plasma-induced "pseudo-photocatalysis". The total (100%) selective plasma-catalytic oxidation of NOx to NO2- and NO3- was achieved at an SIE of 75.3 J/L. The byproduct O3 was effectively degraded and utilized by MnO2, facilitating the deep oxidation of NOx. The facile realization of single atoms would be an ideal way to produce MOF-based catalysts with desired performance. Efficiently combining plasma with single atom-decorated MOF catalysts can provide additional prospects for the plasma-catalytic system. </p

A framework for analyzing playability requirements based on game reviews

Requirements Engineering is an important phase in software development. Game development also requires Requirement Engineering, due to the frequently changes of requirements during the process of the game development [Kasurinen et al., 2014]. However, only a few studies have linked the game development and Requirements Engineering together. Research in related fields is inadequate and needs to be studied in depth Playability is a crucial concept for the game study. For a player, playability is highly related to the player experience, especially the experience of enjoyment. For a video game, the quality of game components affects the degree of playability. Playability is often used for evaluating the video game, but studies focus on playability are insufficient [Korhonen, 2016, p21]. Moreover, few researchers study playability from the perspective of Requirement Engineering. This thesis supposes playability as a kind of non-functional requirements that is important for the game development. The aim of the thesis is to help game designers or testers understand and analyse playability requirements systematically. The thesis work includes two parts, literature review and data analysis. Literature referred to playability, game components and game enjoyment was mainly studied. Based on the literature review, 41 game reviews from GameSpot were collected and analysed by grounded theory. As a result, Playability Framework was developed for understanding and analyzing playability requirements. There are three categories of playability, including Gameplay, Representation and Story. This thesis focuses on Gameplay, since most of data belongs to Gameplay. Furthermore, four elements of Gameplay were concluded, including Goals, Gameworld, Avatar and Player. Through analysing the relationships between the four elements, Gameplay are categorized into three groups, Achievements of goals, Game interaction and Game control. In addition, five attributes that highly affect the quality of gameplay were found during the data analysis, they are Variety, Meaningfulness, Fairness, Pace and Intuitiveness. Based on the framework, the steps of analysing player requirements and the form of playability requirements were also proposed. The result of the thesis can help game designers and testers transfer playability issues into playability requirements, so that the issues can be analyzed and tracked systematically

The Information Content of Option-Implied Volatility for Credit Default Swap Valuation. Working Paper

Abstract Credit default swaps (CDS) are similar to out-of-the-money put options in that both offer a low cost and effective protection against downside risk. This study investigates whether put optionimplied volatility is an important determinant of CDS spreads. Using a large sample of firms with both CDS and options data, we find that individual firms&apos; put option-implied volatility dominates historical volatility in explaining the time-series variation in CDS spreads. To understand this result, we show that implied volatility is a more efficient forecast for future realized volatility than historical volatility. More importantly, the volatility risk premium embedded in option prices covaries with the CDS spread. These findings complement existing empirical evidence based on market-level data

Establishment of a Gene Signature to Predict Prognosis for Patients with Lung Adenocarcinoma

Accumulating evidence indicates that the reliable gene signature may serve as an independent prognosis factor for lung adenocarcinoma (LUAD) diagnosis. Here, we sought to identify a risk score signature for survival prediction of LUAD patients. In the Gene Expression Omnibus (GEO) database, GSE18842, GSE75037, GSE101929, and GSE19188 mRNA expression profiles were downloaded to screen differentially expressed genes (DEGs), which were used to establish a protein-protein interaction network and perform clustering module analysis. Univariate and multivariate proportional hazards regression analyses were applied to develop and validate the gene signature based on the TCGA dataset. The signature genes were then verified on GEPIA, Oncomine, and HPA platforms. Expression levels of corresponding genes were also measured by qRT-PCR and Western blotting in HBE, A549, and PC-9 cell lines. The prognostic signature based on eight genes (TTK, HMMR, ASPM, CDCA8, KIF2C, CCNA2, CCNB2, and MKI67) was established, which was independent of other clinical factors. The risk model offered better discrimination between risk groups, and patients with high-risk scores tended to have poor survival rate at 1-, 3- and 5-year follow-up. The model also presented better survival prediction in cancer-specific cohorts of age, gender, clinical stage III/IV, primary tumor 1/2, and lymph node metastasis 1/2. The signature genes, moreover, were highly expressed in A549 and PC-9 cells. In conclusion, the risk score signature could be used for prognostic estimation and as an independent risk factor for survival prediction in patients with LUAD

The information content of option-implied volatility for credit default swap valuation

Credit default swaps (CDS) are similar to out-of-the-money put options in that both offer a low cost and effective protection against downside risk. This study investigates whether put option-implied volatility is an important determinant of CDS spreads. Using a large sample of firms with both CDS and options data, we find that individual firms' put option-implied volatility dominates historical volatility in explaining the time-series variation in CDS spreads. To understand this result, we show that implied volatility is a more efficient forecast for future realized volatility than historical volatility. More importantly, the volatility risk premium embedded in option prices covaries with the CDS spread. These findings complement existing empirical evidence based on market-level data.Credit default swaps Option implied volatility Historical volatility Price discovery Volatility risk premium

A Calibration Method for Time Dimension and Space Dimension of Streak Tube Imaging Lidar

Owing to the special working systems of streak tube imaging lidar (STIL), the time and space dimensions are coupled together on the streak images. This coupling can cause measurement errors in 3D point clouds and can make measurement results more complicated to calibrate than other kinds of lidars. This paper presents a method to generate a time calibration array and an angle calibration array to separate the offset of the streak into time dimension and space dimension. The time and space information of the signal at any position on the streak image can be indexed through these two arrays. A validation experiment on aircraft was carried out, and the range error of the 3D point cloud was improved from 0.41 m to 0.27 m using the proposed calibration method. Thus, using the proposed calibration method can improve the accuracy of the point cloud produced by STIL

Airborne Streak Tube Imaging LiDAR Processing System: A Single Echo Fast Target Extraction Implementation

In this paper, a ground target extraction system for a novel LiDAR, airborne streak tube imaging LiDAR (ASTIL), is proposed. This system depends on only a single echo and a single data source, and can achieve fast ground target extraction. This system consists of two modules: Autofocus SSD (Single Shot MultiBox Detector) and post-processing. The Autofocus SSD proposed in this paper is used for object detection in the ASTIL echo signal, and its prediction speed exceeds that of the original SSD by a factor of three. In the post-processing module, we describe in detail how the echoes are processed into point clouds. The system was tested on a test set, and it can be seen from a visual perspective that satisfactory results were obtained for the extraction of buildings and trees. The system mAPIoU=0.5 is 0.812, and the FPS is greater than 34. The results prove that this ASTIL processing system can achieve fast ground target extraction based on a single echo and a single data source