Reviewerly/exHarmony huggingface dataset:
Evolving Personalized Content for Super Mario Bros Using Grammatical Evolution

Adapting game content to a particular player's needs and expertise constitutes an important aspect in game design. Most research in this direction has focused on adapting game difficultyto keep the player engaged in the game. Dynamic difficulty adjustment, however, focuses on one aspect of the gameplay experience by adjusting the content to increase ordecrease perceived challenge. In this paper, we introduce a method for automatic level generation for the platform game Super Mario Bros using grammatical evolution. The grammatical evolution-based level generator is used to generate player-adapted content by employing an adaptation mechanism as a fitness function in grammatical evolution to optimizethe player experience of three emotional states: engagement, frustration and challenge. The fitness functions used are models of player experience constructed in our previous work from crowd-sourced gameplay data collected from over 1500 game sessions.
Complex Learning Processes

Abstract : This paper describes the ACT theory of the learning of procedures. ACT is a computer simulation program that uses a propositional network to represent knowledge of general facts and a set of productions (condition action rules) to represent knowledge of procedures. There are currently four different mechanisms by which ACT can make additions and modifications to its set of productions as required for procedural learning: designation, strengthening, generatlization, and discrimination. Designation refers to the ability of productions to call for the creation of new productions. Strengthening a production may have important consequences for performance, since a production's strength determines the amount of system resources that will be allocated to its processing. Finally, generalization and discrimination refer to complementary processes that produce better performance by either extending or restricting the range of situations in which a production will apply. Each of these four mechanisms is discussed in detail and related to the available psychological data on procedural learning. The small-scale simulations of learning provided as examples are drawn from the domains of language processing and computer programming, since our ultimate goal is for ACT to learn the complex procedures required in such domains. (Author)
Hierarchical Parallel Markov Models of Interaction

Finite state techniques are popular in entertainment software production, but they complicate the modeling of certain aspects of social engagement. In this paper we examine the problem of building probabilistic finite-state interaction models that allow both hierarchical composition of behaviors, and their parallel engagement. Finally, we propose an extension that resolves the difficulties for a class of common cases.
Break on Through: An Analysis of Computer Damage Cases

14 Pittsburgh Journal of Technology Law &amp;amp; Policy 158 (2014). This article is an extensive inquiry into computer damage cases based on the comprehensive study of over three hundred cases brought to courts in violation of 18 U.S.C. § 1030(a)(5). Based on an empirical categorization of the essential aspects of computer damage cases, the article analyzes the most relevant issues, interpretations, and arguments available for each computer damage category. These categories include fundamental facets, such as legal elements; motive and intent; results; profile of perpetrators; and means of perpetration, including, if applicable, the software involved.Part I concerns theoretical aspects and discusses the legal elements of computer damage offenses under the CFAA. Part II considers the practical aspects and discusses the essential features involved in the perpetration of these offenses and the profile of attackers. Finally, Part III provides a summary of findings and the implications of this study for stakeholders.This article makes two important contributions: a comprehensive analysis and a conceptual approach for this area. The findings will improve the investigation, prosecution and litigation of such cases in courts, help organizations in their process of identification and mitigation of risks, and stimulate more research in this area. Finally, although this article focused exclusively on one jurisdiction, the findings can be of interest to a wider, global context.
Assistant Agents for Sequential Planning Problems

The problem of optimal planning under uncertainty in collaborative multi-agent domains is known to be deeply intractable but still demands a solution. This thesis will explore principled approximation methods that yield tractable approaches to planning for AI assistants, which allow them to understand the intentions of humans and help them achieve their goals. AI assistants are ubiquitous in video games, mak- ing them attractive domains for applying these planning techniques. However, games are also challenging domains, typically having very large state spaces and long planning horizons. The approaches in this thesis will leverage recent advances in Monte-Carlo search, approximation of stochastic dynamics by deterministic dynamics, and hierarchical action representation, to handle domains that are too complex for existing state of the art planners. These planning techniques will be demonstrated across a range of video game domains.
Quantum Information Theory

If the carriers of information are governed by quantum mechanics, new principles for information processing apply. This graduate textbook introduces the underlying mathematical theory for quantum communication, computation, and cryptography. A focus lies on the concept of quantum channels, understanding fi gures of merit, e.g. fidelities and entropies in the quantum world, and understanding the interrelationship of various quantum information processing protocols.
Detecting Chinese Wish Messages in Social Media: An Empirical Study

People have wishes and sometimes share their wishes in social media, hoping to receive supports or to find partners with the same wishes. By collecting and analyzing those wishes, we may find out not only the trend of common wishes, but also the needs of individuals. This paper presents a preliminary study of Chinese wish detection. We provide analysis on the data from Linkwish, which is a micro social network for wish sharing with users mainly from Taiwan, Hong Kong, and Macao. Then, we use SVM with various types of features to classify these messages as wish or not. Our experimental results show that some features can achieve average areas under precision-recall curves higher than 0:95 in 10-fold cross validation.
Three-dimensional structure from motion recovery of a moving object with noisy measurement

In this paper, a Nonlinear Unknown Input Observer (NLUIO) based approach is proposed for three-dimensional (3-D) structure from motion identification. Unlike the previous studies that require prior knowledge of either the motion parameters or scene geometry, the proposed approach assumes that the object motion is imperfectly known and considered as an unknown input to the perspective dynamical system. The reconstruction of the 3-D structure of the moving objects can be achieved using just two-dimensional (2-D) images of a monocular vision system. The proposed scheme is illustrated with a numerical example in the presence of measurement noise for both static and dynamic scenes. Those results are used to clearly demonstrate the advantages of the proposed NLUIO.
Refiguring digital interventions for energy demand reduction: Designing for life in the digital–material home

This chapter deals with approach to design and intervention that builds on the ability of anthropological ethnography to open up new ways of knowing the world, and that attends to digital media as part of this world. It suggests a reconfiguration of the relationship between theory, research and design intervention that draws on phenomenological anthropology and design research approaches. The chapter explores what happens when the apparent dichotomy of digital presence and affordances and human action and improvisation is both disrupted through ethnographic research and utilized by designers. Social scientists in particular have been critical of both the utopian notion of digital technologies as providing all answers to energy demand reduction questions, and of the simplicity of the above human/technological agency dichotomy.
Software Process: Applying Industrial Strength Methods In Engineering Education

Improving productivity and quality in software development is one of the major concerns of the software engineering discipline, as software systems grow to millions, and soon billions, of lines of code.Productivity and defect density levels that are considered very good today will be inadequate to keep up with this future growth.As a result, software development professionals and organizations are striving to improve existing processes and to develop new ones.One example of demonstrated benefits from these efforts is the success of the Personal Software Process (PSP) and the Team Software Process (TSP) developed by the Software Engineering Institute (SEI) at Carnegie Mellon University.This paper discusses the structure of the TSP and PSP processes, industry experiences with their application, and their relationship to other process improvement frameworks, including the current version of the SEI's Capability Maturity Model (now known as CMMI).With this background, it reflects on the introduction of the PSP and TSP into software engineering curricula, and reports experiences at the Milwaukee School of Engineering, one of the first four ABET-accredited software engineering programs.
Reinforcement Learning for Spatial Reasoning in Strategy Games

One of the major weaknesses of current real-time strategy (RTS) game agents is handling spatial reasoning at a high level. One challenge in developing spatial reasoning modules for RTS agents is to evaluate the ability of a given agent for this competency due to the inevitable confounding factors created by the complexity of these agents. We propose a simplified game that mimics spatial reasoning aspects of more complex games, while removing other complexities. Within this framework, we analyze the effectiveness of classical reinforcement learning for spatial management in order to build a detailed evaluative standard across a broad set of opponent strategies. We show that against a suite of opponents with fixed strategies, basic Q-learning is able to learn strategies to beat each. In addition, we demonstrate that performance against unseen strategies improves with prior training from other distinct strategies. We also test a modification of the basic algorithm to include multiple actors, to speed learning and increase scalability. Finally, we discuss the potential for knowledge transfer to more complex games with similar components.
Design Of A Cooperative Autonomous Mobile Robot System At The Undergraduate Level

This paper describes an undergraduate-level design project in a course on autonomous mobile robot systems.The project is intended to allow a great deal of latitude in implementation and to promote teamwork and integrated design methodologies in a framework that is both instructional and interesting.The technical challenges of the project include limited bandwidth communications, cooperative multi-agent algorithms, data storage and transmission and physical system design/control.Additionally, the project is structured in such a way as to provide the students experience in organizing large teams of cooperative designers and working with small task-dedicated design teams.
A Practice-Oriented Approach to Teaching Undergraduate Data Mining Course

Data mining is a fast-growing field of study in Computer Science and Information Systems.Many schools have developed data mining course for undergraduate students.The course content has been well defined and streamlined because of the availability of outstanding data mining textbooks.However, the focus on theoretical contents of data mining makes it hard for undergraduate students to digest, and thus, compromises the overall learning outcome.To create an effective and dynamic learning environment, we introduce a practice-oriented approach.This paper describes how we integrate the hands-on component into the course work to enhance the learning of the core data mining topics including data preprocessing, association mining, classification, cluster analysis, text mining, and visualization.The open-source data mining tool, RapidMiner, is introduced to assist students to explore and digest various data mining processes and algorithms.Overall, the hands-on experience provides students a better insight into data mining functions.
Hierarchical Estimation Framework of Multi-Label Classifying: A Case of Tweets Classifying into Real Life Aspects

Many people share their daily events and opinions on Twitter. Some are beneficial and comment on several aspects of a user’s real life, i.e., eating, traffic conditions, weather, and so on. Since some tweets indicate two or more aspects, multi-label classification is required. Typical methods are not performed on tweets because they consist of short and elided sentences. To conquer these problems, we are researching a hierarchical estimation framweork (HEF) to estimate several aspects of unknown tweets. HEF is composed of both unsupervised and supervised machine learnings. In the first phase, it extracts topics from a sea of tweets using latent dirichlet allocation (LDA). In the second phase, it calculates the relevance between topcis and aspects using a small set of labeled tweets to build associations among them. In this paper, we introduce the entropy feedback method in the second phase. We evaluate the Shannon entropy of each association between the aspects and topics and iteratively calculate the feedback coefficients by entropy to achieve optimal associations. Our sophisticated experimental evaluations with a large amount of actual tweets demonstrate the high efficiency of our multi-labeling method. Our entropy feedback method successfully increased higher F-measures in all aspects. Expecially in Disaster and Traffic aspects, precision greatly increased without decreasing recall.
7. Model-theoretic semantics

Model-theoretic semantics is a special form of truth-conditional semantics. According to it, the truth-values of sentences depend on certain abstract objects called models. Understood in this way, models are mathematical structures that provide the interpretations of the (non-logical) lexical expressions of a language and determine the truth-values of its (declarative) sentences. Originally designed for the semantic analysis of mathematical logic, model-theoretic semantics has become a standard tool in linguistic semantics, mostly through the impact of Richard Montague’s seminal work on the analogy between formal and natural languages. As such, it is frequently (and loosely) identified with possible worlds semantics, which rests on an identification of sentence meanings with regions in Logical Space, the class of all possible worlds. In fact, the two approaches have much in common and are not always easy to keep apart. In a sense, (i) model-theoretic semantics can be thought of as a restricted form of possible worlds semantics, where models represent possible worlds; in another sense, (ii) model-theoretic semantics can be seen as a wild generalization of possible worlds semantics, treating Logical Space as variable rather than given. Consequently, the present introductory exposition of model-theoretic semantics also covers possible worlds semantics - hopefully helping to disentangle the relationship between the two approaches. It starts with a general discussion of truth-conditional semantics (section 1), the main purpose of which is to provide some motivation and background. Model- theoretic semantics is then approached from the possible worlds point of view (section 2), highlighting the similarities between the two approaches that give rise to perspective (i). The final section 3 turns to model theory as providing a mathematical reconstruction of possible worlds semantics, ultimately arriving at the more abstract perspective (ii).
9. Situation Semantics and the ontology of natural language

Situation Semantics emerged in the 1980s with an ambitious program of reform for semantics, both in the domain of semantic ontology and with regard to the integration of context in meaning. This article takes as its initial focus the topic of a situation-based ontology, more generally discussing the approach to NL ontology that emerged from situation semantics. The latter part of the article will explain how recent work synthesizing situation semantics with type theory enables the original intuitions from situation semantics to be captured in a dynamic, computationally tractable framework.
3. Frame Semantics

Frames are conceptual structures that provide context for elements of interpretation; their primary role in an account of text understanding is to explain how our text interpretations can leap far beyond what the text literally says. The present article explores the role of frames in providing a principled account of the openness and richness of word-meanings, distinguishing a framebased account from classical approaches, such as accounts based on conceptual primitives, lexical fields, and connotation, and showing how they can play a role in the account of how word meaning interacts with syntactic valence.
ENGINEERING 2D BAR CODE SYMBOLOGIES FOR MANUFACTURING INFORMATION SYSTEM MANAGEMENT

Two-dimensional (2D) bar codes literally add another dimension to engineering information management systems when compared to the common linear bar code symbol. The power of the 2D symbol is in its' design and application use. First, a 2D bar code symbology allows a single, complete information record (up to millions of characters) to move with the product, process, or shipment. The second significant attribute involving 2D symbologies is the use of error correction. Simply put, the ability of a bar code symbology to use error correction allows the symbology in question to be partially destroyed or damaged and still be completely readable by an input device. This paper will address three of the most commonly used 2D bar code symbologies based on usage, standards, public access, and application use. The three 2D bar code symbologies that will be discussed include PDF417, DataMatrix, and MaxiCode. Mathematical descriptions and applications as they related to manufacturing environments will be the focus.
Evaluating RBMT output for -ing forms: A study of four tar-get languages

-ing forms in English are reported to be problematic for Machine Transla-tion and are often the focus of rules in Controlled Language rule sets. We investigated how problematic -ing forms are for an RBMT system, translat-ing into four target languages in the IT domain. Constituent-based human evaluation was used and the results showed that, in general, -ing forms do not deserve their bad reputation. A comparison with the results of five automated MT evaluation metrics showed promising correlations. Some issues prevail, however, and can vary from target language to target lan-guage. We propose different strategies for dealing with these problems, such as Controlled Language rules, semi-automatic post-editing, source text tagging and “post-editing” the source text.
THE EFFECT OF GENRE-BASED APPROACH AND LEARNER AUTONOMY ON THE WRITING COMPETENCE OF THE EIGHTH GRADE STUDENTS OF SMP HARAPAN NUSANTARA

This study aimed at: a) finding out whether or not there is a significant difference in writing competence between the students who were taught by using genre based approach and those who were taught by using a conventional strategy; b) finding out whether or not there is an effect of the interaction between the implementation of genre based approach and learner autonomy on the students writing competence; 3) finding out whether or not there is a significant difference in writing competence between the students with high autonomy treated by using genre based approach and those treated by using a conventional strategy; 4) finding out whether or not there is a significant difference in writing competence between the students with how autonomy who were treated by using genre based approach and those treated by using a conventional strategy. The study employed a post test for control group and an experiment group with 2 x 2 factorial designs. The population of the study was 196 eighth grade students of SMP Harapan Nusantara in academic year 2015/2016 where 144 of them were selected as the sample of the study through cluster random sampling technique. The data were collected by means of attitude questionnaire and writing competence test and were analyzed by using Two-Way ANOVA and Tukey test. The result of this research showed that: a) there was significant difference in writing competence between the students who are taught by using genre based approach and those who are taught by using a conventional strategy, b) there was significant effect of the interaction between the implementation of genre based approach and learner autonomy on the students’ writing competence, c) there was significant difference in writing competence between the students with high autonomy treated by using genre based approach and those treated by using a conventional strategy and d) there was significant difference in writing competence between the students with low autonomy who are treated by using genre based approach and those treated by using a conventional strategy. The implication of this study reveals that a Genre-Based Approach is useful approach for supporting students’ development.
PERAN EXPERIENCED STIGMA TERHADAP SELF ESTEEM PADA SUKU NIAS

S This study aims to determine the role of experienced stigma against self esteem in Nias ethnic. The study involved 151 people of Nias ethnic who lived in Medan. Sampling was done by incidental sampling and processed by simple linear regression test with an SPSS 17.0 Software Program. The instrument in this research are the scale of experienced stigma and self-esteem scale developed by the researchers.These results indicate there is the role of experienced stigma against self esteem in Nias ethnic (R = 0.577; R 2 = 0.333; p = 0.000 &lt;0.05), which means that the experienced stigma cast by 33.3% to self esteem in Nias ethnic. Then, result from this study find that experienced stigma in Nias ethnic is positive, which means that they don’t form a negative assessment toward themself even they are stigmatized, so their self esteem do not get lowered. Keywords : Experienced Stigma, Self Esteem, Nias Ethnic ABSTRAK Penelitian ini bertujuan untuk mengetahui peran experienced stigma terhadap self esteem pada suku Nias. Penelitian ini melibatkan 151 orang suku Nias yang berdomisili di Medan. Pengambilan sampel dilakukan dengan incidental sampling dan diolah dengan uji regresi linier sederhana dengan bantuan SPSS 17.0 for windows . Alat ukur yang digunakan adalah skala experienced stigma dan skala self esteem yang disusun oleh peneliti. Hasil penelitian ini menunjukkan terdapat peran experienced stigma terhadap self esteem pada suku Nias (R= 0,577; R2= 0,333; p=0,000 &lt; 0,05), peran yang diberikan experienced stigma terhadap self esteem suku Nias adalah sebesar 33,3%. Selanjutnya, pada hasil penelitian ini didapatkan bahwa experienced stigma suku Nias berada dalam kategori yang positif, yang artinya adalah mereka tidak membentuk penilaian negatif terhadap dirinya sendiri meskipun terstigma, sehingga tidak menurunkan self esteem suku Nias yang menjadi subjek penelitian ini. Kata kunci : Experienced Stigma, Self Esteem, Suku Nias