Strategic Abilities of Forgetful Agents in Stochastic Environments

In this paper, we investigate the probabilistic variants of the strategy logics ATL and ATL* under imperfect information. Specifically, we present novel decidability and complexity results when the model transitions are stochastic and agents play uniform strategies. That is, the semantics of the logics are based on multi-agent, stochastic transition systems with imperfect information, which combine two sources of uncertainty, namely, the partial observability agents have on the environment, and the likelihood of transitions to occur from a system state. Since the model checking problem is undecidable in general in this setting, we restrict our attention to agents with memoryless (positional) strategies. The resulting setting captures the situation in which agents have qualitative uncertainty of the local state and quantitative uncertainty about the occurrence of future events. We illustrate the usefulness of this setting with meaningful examples

An investigation of mobile augmented reality-based learning features in cognitive and affective environments

This research focuses on the effectiveness of using mobile Augmented Reality (mAR) for learning. Prior research has focused primarily on developing virtual contents for Augmented Reality (AR) and has largely ignored AR in the mobile context. Herein, this research primarily aims to examine the effectiveness of learning through two modes: mobile Augmented Reality (mAR) and the Current Learning Mode (CLM). This research is extended to the development stage of a theoretical model, to evaluate the ability of mAR in improving the learning outcomes that guide a further consideration of growth in learning. The first phase of this thesis is to examine the impact of how mAR influences the learning outcomes in cognitive ability and affective learning outcomes. The cognitive outcome was measured by the experimental method of using pre/ post-test performance achievement, while the affective learning outcome was measured by perceived usefulness, self-efficacy and satisfaction. This research contributes to cognitive ability and affective learning by investigating the differences in the learning outcomes and performance achievements of mAR within a self-centred learning environment, a classroom. The findings show that students’ performance achievement, learning outcomes, perceived learning effectiveness and self-efficacy were greater in the mAR group, as compared to the CLM group. Second, a theoretical model was developed and analysed using Structural Equation Modelling (SEM). SEM examines significant relationships between the determinants that integrate and facilitate effective mAR-based learning environments. SEM produces a feasible alternative in measuring the causal relationship amongst the constructs. This model evaluates to implement mAR as a learning aid in student-centred learning and to evaluate the motivation among students through the features of mAR, due to the absence of an in-depth understanding of the motivation of mAR-based learning from the current literature. This model also provides an insight into the causal factors amongst the dimensions of mAR. Finally, in the model, the moderating effects of students’ characteristics, which include their experience and age, are investigated to determine the factors influencing mAR. The findings of this research will help to verify the learning effectiveness of mAR, to improve the learning experiences, learning outcomes and performance achievements of students. Based on the results, it is confirmed that mAR can be leveraged upon and used as an optimum learning tool, exemplifying the use of technology within an educational context. In the aspects of information retention and learning outcome enhancement, mAR is significant in education as it facilitates students’ understanding by supporting abstract ideas throughout the course, enabling the students to learn in a limited period. Based on the results, it can be concluded that mAR is a technology that aids students with a better understanding of the subject matter and hence, resulting in greater motivation. With regards to the model fitness via the analysis of goodness-of-fit, all the results are confirmed as appropriate and good fit. Also, the model also shows a positive causal path from the mAR features’ determinant. The thesis can also assist educational administrators and educational policy makers in gauging the importance of mAR as a learning tool. This helps mainly to overcome the issue of educators being criticised for the lack of real-life experience that is being exposed to students at the university level. Furthermore, academia can use the model’s findings as appropriate groundwork to initiate other related studies, and this will help to fill the gap in the mAR learning area

Human performance in agile production systems : a longitudinal study in system outcomes, human cognition, and quality of work life.

This dissertation examines a research objective associated with human performance in agile production systems, with specific attention towards the hypothesis that system outcomes are the causal result of worker human cognition and quality of work life attributes experienced in an agile production system. The development and adoption of world class agile production systems has been an immediate economic answer to the world-wide competitive call for more efficient, more cost-effective, and more quality laden production processes, but has the human element of these processes been fully understood and optimized? Outstanding current literature suggests that the recent movements toward higher standards in systems outcomes (i.e. increased quality, decreased costs, improved delivery schedules, etc) has not been truly evaluated. The human-machine interaction has not been fully comprehended, not to mention quantified; the role of human cognition is still under evaluation; and the coupling of the entire production system with respect to the human quality of life has yielded conflicting messages. The dissertation research conducted a longitudinal study to evaluate the interrelationships occurring between system outcomes, applicable elements of human cognition, and the quality of work life issues associated with the human performance in agile production systems. A structural equation modeling analysis aided the evaluation of the hypotheses of the dissertation by synthesizing the three specific instruments measuring the appropriate latent variables: 1. system outcomes – empirical data, 2. human cognition – cognitive task analysis, and 3. quality of work life – questionnaires into a single hypothesized model. These instruments were administered in four (4) waves during the eight month longitudinal study. The study latent variables of system outcomes, human cognition, and quality of work life were shown to be quantifiable and causal in nature. System outcomes were indicated to be a causal result of the combined, yet uncorrelated, effect of human cognition and quality of work life attributes experienced by workers in agile production systems. In addition, this latent variable relationship is situational, varying in regards to the context of, but not necessarily the time exposed to, the particular task the worker is involved with. An implication of this study is that the quality of work life attributes are long-term determinants of human performance, whereas human cognition attributes are immediate, activity based determinants of human performance in agile production systems

Loop-Abort Faults on Lattice-Based Fiat–Shamir and Hash-and-Sign Signatures

As the advent of general-purpose quantum computers appears to be drawing closer, agencies and advisory bodies have started recommending that we prepare the transition away from factoring and discrete logarithm-based cryptography, and towards postquantum secure constructions, such as lattice- based schemes. Almost all primitives of classical cryptography (and more!) can be realized with lattices, and the efficiency of primitives like encryption and signatures has gradually improved to the point that key sizes are competitive with RSA at similar security levels, and fast performance can be achieved both in soft- ware and hardware. However, little research has been conducted on physical attacks targeting concrete implementations of postquantum cryptography in general and lattice-based schemes in particular, and such research is essential if lattices are going to replace RSA and elliptic curves in our devices and smart cards. In this paper, we look in particular at fault attacks against implementations of lattice-based signature schemes, looking both at Fiat–Shamir type constructions (particularly BLISS, but also GLP, PASSSing and Ring-TESLA) and at hash-and-sign schemes (particularly the GPV-based scheme of Ducas–Prest– Lyubashevsky). These schemes include essentially all practical lattice-based signatures, and achieve the best efficiency to date in both software and hardware. We present several fault attacks against those schemes yielding a full key recovery with only a few or even a single faulty signature, and discuss possible countermeasures to protect against these attacks

Factors that motivate South African students to share fake news on social media platforms

Dissertation (MIT (Information Systems) )--University of Pretoria, 2021.The increased adoption of social media and the continued spread of fake news has resulted in unique problems for society to overcome in the modern era. This study aims to determine what factors influence South African students to share fake news on social media platforms. The theory that was used to create the research model and questionnaire was the Users and Gratification (U&G) framework. A mixed-method approach was followed in conducting the study, utilising both quantitative and qualitative strategies. Data was gathered through collecting responses using a questionnaire distributed to students of the EBIT faculty at the University of Pretoria. 190 usable responses were gathered. The questionnaire was created using Google forms and the questionnaire link was shared to students through clickUP and various student groups on Facebook. The factors that were investigated were platform, emotional drivers, social responsibility, conformity, biases, trust, third-person perspective (TPP) and personality and how they influence intention to share fake news among students. The findings from the empirical study of 190 students found that the hypothesis that there is a positive association between bias and trust was partially supported. There was also found to be a negative correlation between third-person perspective, emotional drivers, and the conscientiousness trait of the big-five personality model. This confirms that people’s emotional drive, bias, TPP, trust, and conscientiousness have a moderate effect on their intention to share. Additionally, from the qualitative findings, the factors of previous experience and knowledge were also found to influence intention to share. Through partial least squares regression analysis, we found that the factors that contributed the most to intention to share are emotional influences and the conscientiousness trait of personality that both had a negative association. TPP has small correlations to intention to share. Trust and bias were removed from the quantitative model due to bad fit, however, from the qualitative findings it was determined that trust and bias impacted students’ identification of fake news articles. By understanding the relationship between TPP, conscientiousness, trust, bias, emotional drivers, previous experience, previous knowledge and intention to share fake news may help further the understanding of why fake news is spread, the motivation for students to share fake news and curb the spread with changing technological environments. These findings can also promote action to implement programs and regulations to protect users who are vulnerable and more exposed to fake news on social media platforms.InformaticsMIT (Information Systems)Unrestricte

Personalizable Knowledge Integration

Large repositories of data are used daily as knowledge bases (KBs) feeding computer systems that support decision making processes, such as in medical or financial applications. Unfortunately, the larger a KB is, the harder it is to ensure its consistency and completeness. The problem of handling KBs of this kind has been studied in the AI and databases communities, but most approaches focus on computing answers locally to the KB, assuming there is some single, epistemically correct solution. It is important to recognize that for some applications, as part of the decision making process, users consider far more knowledge than that which is contained in the knowledge base, and that sometimes inconsistent data may help in directing reasoning; for instance, inconsistency in taxpayer records can serve as evidence of a possible fraud. Thus, the handling of this type of data needs to be context-sensitive, creating a synergy with the user in order to build useful, flexible data management systems. Inconsistent and incomplete information is ubiquitous and presents a substantial problem when trying to reason about the data: how can we derive an adequate model of the world, from the point of view of a given user, from a KB that may be inconsistent or incomplete? In this thesis we argue that in many cases users need to bring their application-specific knowledge to bear in order to inform the data management process. Therefore, we provide different approaches to handle, in a personalized fashion, some of the most common issues that arise in knowledge management. Specifically, we focus on (1) inconsistency management in relational databases, general knowledge bases, and a special kind of knowledge base designed for news reports; (2) management of incomplete information in the form of different types of null values; and (3) answering queries in the presence of uncertain schema matchings. We allow users to define policies to manage both inconsistent and incomplete information in their application in a way that takes both the user's knowledge of his problem, and his attitude to error/risk, into account. Using the frameworks and tools proposed here, users can specify when and how they want to manage/solve the issues that arise due to inconsistency and incompleteness in their data, in the way that best suits their needs

Managerial wealth, behavioural biases and corporate monitoring : impact on managerial risk taking and value creation in UK high-tech and low-tech acquisitions

While the traditional agency model assumes managerial risk aversion and underinvestment in high-risk opportunities, the behavioural agency model allows for risk seeking by managers leading possibly to over-risky investments. Corporate governance mechanisms through their disciplining roles can steer managers towards optimal risk and avoid value destruction from either risk-deficit or risk-excess on the part of their managers. None of the existing studies offer a complete picture of managerial risk taking by allowing for both managerial risk aversion and risk seeking. The painting of just such a picture is the primary focus of this thesis. This thesis aims to answer the following two research questions in the context of corporate acquisitions: 1. What are the factors that drive managers to undertake risky projects? 2. To what extent is firm performance related to the optimal or suboptimal risk level of an investment project? This thesis investigates 289 UK domestic high-tech acquisitions and 289 matching low-tech acquisitions over the period 1993-2000. High-tech acquisitions are argued to be riskier than low-tech acquisitions. This thesis documents that fixed compensation, annual bonus, and LTIP cash provide few incentives for managers to conduct risky acquisitions. It finds significant evidence that equity-based wealth (such as LTIP shares, stock options and managerial shareholdings) which links managers' wealth to firm stock performance, has a nonlinear incentive effect on managers' selection of acquisition risk. At a low level, it encourages managers to pursue risky acquisitions. However, at high levels it discourages managerial risk taking. This nonlinear effect is mainly contributed to by managerial shareholdings. No evidence is found that stock options make managers select riskier acquisitions. Strong evidence is found that a high level of managerial wealth, which induces managerial risk aversion, can weaken the incentive alignment effect of equitybased wealth. This thesis finds significant evidence that managerial behavioural biases (such as overconfidence, over-optimism, and hubris) boosted by good past performance, firm glamour ratings by the stock market and a flattering media profile induce managers to engage in risky high-tech acquisitions. Corporate monitors are generally ineffective in disciplining managers' selection of acquisition risk. Overall, this thesis concludes that what makes managers take risky acquisitions appears to be the internal factors, i. e., factors that work within managers' inner selves and give them more confidence that they can control risks. External factors such as corporate monitoring devices that try to control managerial behaviour, do not necessarily boost managers' confidence in their risk managing capabilities. Regarding post-acquisition performance, this thesis documents that UK hightech acquisitions in the 1990s do not bring any value to acquirer shareholders up to three years after acquisition completion. However, high-risk high-tech acquisitions do not necessarily destroy more shareholder value than low-risk low-tech acquisitions. Acquisitions that are identified as at 'optimal' risk level perform better than under-risk acquisitions. Indeed, more shareholder value is created in acquisitions that are over-risk than acquisitions that are either optimal-risk or under-risk. Therefore, this thesis suggests that many UK acquirer managers during the period over 1993-2000 have foregone valuable but high risk growth opportunities and destroyed shareholder value more by being excessively risk-averse rather than being adventurous in their risk choices.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

An Epistemic Strategy Logic

This article presents an extension of temporal epistemic logic with operators that can express quantification over agent strategies. Unlike previous work on alternating temporal epistemic logic, the semantics works with systems whose states explicitly encode the strategy being used by each of the agents. This provides a natural way to express what agents would know were they to be aware of some of the strategies being used by other agents. A number of examples that rely on the ability to express an agent’s knowledge about the strategies being used by other agents are presented to motivate the framework, including reasoning about game-theoretic equilibria, knowledge-based programs, and information-theoretic computer security policies. Relationships to several variants of alternating temporal epistemic logic are discussed. The computational complexity of model checking the logic and several of its fragments are also characterized