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Purpose Cybersecurity vulnerabilities are often due to human users acting according to their own ethical priorities. With the goal of providing tailored training to cybersecurity professionals, the authors conducted a study to uncover profiles of human factors that influence which ethical principles are valued highest following exposure to ethical dilemmas presented in a cybersecurity game.Design/methodology/approach The authors’ game first sensitises players (cybersecurity trainees) to five cybersecurity ethical principles (beneficence, non-maleficence, justice, autonomy and explicability) and then allows the player to explore their application in multiple cybersecurity scenarios. After playing the game, players rank the five ethical principles in terms of importance. A total of 250 first-year cybersecurity students played the game. To develop profiles, the authors collected players' demographics, knowledge about ethics, personality, moral stance and values.Findings The authors built models to predict the importance of each of the five ethical principles. The analyses show that, generally, the main driver influencing the priority given to specific ethical principles is cultural background, followed by the personality traits of extraversion and conscientiousness. The importance of the ingroup was also a prominent factor.Originality/value Cybersecurity professionals need to understand the impact of users' ethical choices. To provide ethics training, the profiles uncovered will be used to build artificially intelligent (AI) non-player characters (NPCs) to expose the player to multiple viewpoints. The NPCs will adapt their training according to the predicted players’ viewpoint.

Morals are an important part of many stories, and central to why storytelling developed in the first place as a means of communication. They have the potential to provide a framework for developing story structure, which could be utilised by modern storytelling systems. To achieve this we need a general representation for morals. We propose patterns of character emotion as a suitable foundation. In this paper, we categorise Aesop’s fables based on the morals they convey, and use them as a source of emotion data corresponding to those morals. We use inductive logic programming to identify relationships between particular patterns of emotion and the morals of the stories in which they arise.

Narrative AI needs to model more than just action. In this paper, we investigate the Belief-Desire-Intention (BDI) agent architecture to allow plots to be modelled in terms of character motivation. This allows authors to focus on elements of the character model which are highly relevant to plot. We describe an extended implementation of the ConGolog agent programming language which includes BDI syntax and semantics. Using this language, we provide an example of how plot could be advantageously modelled in terms of character motivation.

As robots and Artificial Intelligences become more enmeshed in rich social contexts, it seems inevitable that we will have to make them into moral machines equipped with moral skills. Apart from the technical difficulties of how we could achieve this goal, we can also ask the ethical question of whether we should seek to create such Artificial Moral Agents (AMAs). Recently, several papers have argued that we have strong reasons not to develop AMAs. In response, we develop a comprehensive analysis of the relevant arguments for and against creating AMAs, and we argue that all things considered we have strong reasons to continue to responsibly develop AMAs. The key contributions of this paper are threefold. First, to provide the first comprehensive response to the important arguments made against AMAs by Wynsberghe and Robbins (in “Critiquing the Reasons for Making Artificial Moral Agents”, Science and Engineering Ethics 25, 2019) and to introduce several novel lines of argument in the process. Second, to collate and thematise for the first time the key arguments for and against AMAs in a single paper. Third, to recast the debate away from blanket arguments for or against AMAs in general, to a more nuanced discussion about the use of what sort of AMAs, in what sort of contexts, and for what sort of purposes is morally appropriate.

Introduction: The addition of durvalumab after chemoradiation therapy (CRT) in unresectable stage III NSCLC significantly improves survival. The benefit of this approach in elderly patients is controversial given the toxicity associated with CRT and, thus, may be underutilized. We sought to investigate the outcomes of elderly patients treated with CRT without or without durvalumab at our center. Methods: We reviewed all stage III patients with NSCLC treated with CRT between 2018 and 2020. Patients were analyzed on the basis of age: less than 70 years and 70 years and older. The end points evaluated were treatment patterns, toxicity, progression-free survival, and overall survival. Results: The baseline characteristics including Eastern Cooperative Oncology Group performance status and comorbidities were similar among the 115 patients (44 elderly, 71 young). Completion rates of CRT (100%, 97%) and chemotherapy dose intensity (97%, 97%) were high in elderly and young patients, respectively. There was a trend toward increased hospitalizations in elderly patients because of infections (27% versus 13%, p = 0.08). Of those who did not have primary progression after CRT, 78% of eldery and 81% of young patients received durvalumab. The incidence of grade 3 or higher immune-related adverse events was 9% in elderly and 6% in young patients (p = 0.67). The median progression-free survival was similar (15.6 versus 10.5 mo, p = 0.10), even after adjusting for comorbidities (hazard ratio = 0.6, p = 0.09). The 12-month overall survival rates were 78% in the elderly and 76% in young patients (p = 0.98). Conclusions: Well-selected elderly patients can be treated safely with CRT followed by durvalumab with similar survival benefits compared with their younger counterparts. We would advocate for the referral of all elderly patients for oncologic assessment to avoid undertreatment.

According to cognitive psychologists, moral decision-making is a dual-process phenomenon involving two types of cognitive processes: explicit reasoning and implicit intuition. Moral development involves training and integrating both types of cognitive processes through a mix of instruction, practice, and reflection. Serious games are an ideal platform for this kind of moral training, as they provide safe spaces for exploring difficult moral problems and practicing the skills necessary to resolve them. In this article, we present Morality Play, a model for the design of serious games for ethical expertise development based on the Integrative Ethical Education framework from moral psychology and the Lens of the Toy model for serious game design.

Introduction: Durvalumab immunotherapy has rapidly emerged as standard treatment for stage 3 NSCLC patients following definitive chemoradiotherapy (CRT). Multiple novel immunotherapeutic strategies are in development to enhance the chance of cure in this setting as well. There exists a critical need to identify blood-based biomarkers capable of predicting clinical benefit from adjuvant immunotherapy as well selecting patients at high-risk of relapse for further drug development. Cell-free DNA (cfDNA)-based analysis of both minimal residual disease (MRD) and T-cell receptor (TCR) clonality have immense potential to predict and monitor response to adjuvant immunotherapy. In this study, we have combined innovative cfDNA measures of MRD (CAPPseq), TCR clonality (CapTCR-seq) and methylation (cfMeDIPseq) as potential predictive biomarkers of disease progression in stage 3 NSCLC patients treated with CRT and durvalumab. Methods: Stage 3 NSCLC patients undergoing CRT and durvalumab were recruited prospectively to undergo serial blood collections at baseline, pre- and post- durvalumab. CAPPseq and cfMeDIPseq were performed as measures of MRD. TCR repertoire analysis (CapTCR-seq) was performed on cfDNA using hybrid-capture TCR sequencing and TCR diversity/clonality was estimated using the Shannon's index. Correlations between MRD, TCR clonality, response and progression-free survival (PFS) were examined using logistic/cox regression. Results: 79 stage 3 NSCLC patients have been prospectively recruited and undergone serial blood collection. CAPPseq, cfMeDIPseq and capTCR-seq have been completed in 22 patients (5 primary progression on CRT, 17 received durvalumab). Tumor cfDNA was detectable by CAPPseq at baseline in 14 patients. High correlation between tumor cfDNA detected by CAPPseq and cfMeDIPseq was found (R=0.68, p Conclusions: Failure to clear MRD and decreasing TCR clonality as assessed by cfDNA was highly correlated with increased risk of recurrence and reduced PFS with consolidation durvalumab. This innovative approach has significant potential to define a new biomarker for the use and development of adjuvant immunotherapy. Citation Format: Sally CM Lau, Shirin Soleimani, Jinfeng Zou, Justin Burgener, Shelley Kuang, Stephanie WY Wong, Malcolm Ryan, Ben X. Wang, Stephanie Pedersen, Devalben Patel, Penelope A. Bradbury, Geoffrey Liu, Natasha Leighl, Ming S. Tsao, Pamela S. Ohashi, Scott V. Bratman, Trevor Pugh, Frances A. Shepherd, Adrian G. Sacher. cfDNA-based analysis of minimal residual disease and T-cell receptor clonality as predictors of relapse in stage 3 NSCLC treated with chemoradiotherapy and durvalumab [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 563.

This special issue of Games and Culture focuses on the intersection between video games and ethics. This introduction briefly sets out the key research questions in the research field and identifies trends in the articles included in this special issue.

Tablet computer displays are amenable for the development of vision tests in a portable form. Assessing color vision using an easily accessible and portable test may help in the self-monitoring of vision-related changes in ocular/systemic conditions and assist in the early detection of disease processes. Tablet computer-based games were developed with different levels of gamification as a more portable option to assess chromatic contrast sensitivity. Game 1 was designed as a clinical version with no gaming elements. Game 2 was a gamified version of game 1 (added fun elements: feedback, scores, and sounds) and game 3 was a complete game with vision task nested within. The current study aimed to determine the normative values and evaluate repeatability of the tablet computer-based games in comparison with an established test, the Cambridge Colour Test (CCT) Trivector test. Normally sighted individuals [N = 100, median (range) age 19.0 years (18-56 years)] had their chromatic contrast sensitivity evaluated binocularly using the three games and the CCT. Games 1 and 2 and the CCT showed similar absolute thresholds and tolerance intervals, and game 3 had significantly lower values than games 1, 2, and the CCT, due to visual task differences. With the exception of game 3 for blue-yellow, the CCT and tablet computer-based games showed similar repeatability with comparable 95% limits of agreement. The custom-designed games are portable, rapid, and may find application in routine clinical practice, especially for testing younger populations.

Papers, Please, by Lucas Pope (2013), explores the story of a customs inspector in the fictional political regime of Arstotzka. In this paper we explore the stories, systems and moral themes of Papers, Please in order to illustrate the systemic approach to designing videogames for moral engagement. Next, drawing on the Four Component model of ethical expertise from moral psychology, we contrast this systemic approach with the more common scripted approach. We conclude by demonstrating the different strengths and weaknesses that these two approaches have when it comes to designing videogames that engage the different aspects of a player's moral expertise.

Historically the focus of moral decision-making in games has been narrow, mostly confined to challenges of moral judgement (deciding right and wrong). In this paper, we look to moral psychology to get a broader view of the skills involved in ethical behaviour and how these skills can be employed in games. Following the Four Component Model of Rest and colleagues, we identify four “lenses” – perspectives for considering moral gameplay in terms of focus, sensitivity, judgement and action – and describe the design problems raised by each. To conclude, we analyse two recent games, The Walking Dead and Papers, Please, and show how the lenses give us insight into important design differences between these games.

In this paper we investigate three different approaches to encoding domain-dependent control knowledge for Answer-Set Planning. Starting with a standard imple- mentation of the action description language B, we add control knowledge expressed in the GOLOG logic pro- gramming language. A naive encoding, following the original definitions of Levesque et al., is shown to scale poorly. We examine two alternative codings based on the transition semantics of ConGOLOG. We show that a speed increase of multiple orders of magnitude can be obtain by compiling the GOLOG program into a finite- state machine representation.

In its strategic plan, the University of Greenwich envisages a significant shift to resource-based learning (RBL). Enterprise in Higher Education (EHE) has funded five pilot RBL projects during the past year, including one in introductory economics. The project was managed by three lecturers in the School of Social Sciences, supported by an Academic Development Officer. Learning outcomes were completely revised, and a range of assessment strategies, including computer-based tests, was identified. A resources guide was produced which identified the materials and activities that would enable students to achieve the learning outcomes. A number of innovations were adopted, including: • computer-based curriculum delivery, assessment, and student evaluation of the course; • an open approach to assessment; • abolishing lectures in favour of a diverse range of teaching and learning activities.DOI:10.1080/0968776960040114

In traditional computer role-playing games (CRPGs), vendors are merchants who trade with players. Until now, these games have used vendors with static pricing or extremely simple pricing models, and this has hindered player immersion. In an effort to solve this problem, we present Crafty, a tool allowing developers to easily implement dynamic pricing mechanics for their games' vendors. Crafty studies player demand and chooses prices so as to maximise the profit. It thus allows CRPGs to be populated by vendors with intelligence, personality and intent, while requiring minimal effort by developers. Play-testing results show that players perceive such vendors more as fellow characters than as vending machines, improving the experience of the role-play.

Multi-robot path planning is difficult due to the combinatorial explosion of the search space with every new robot added. Complete search of the combined state-space soon becomes intractable. In this paper we present a novel form of abstraction that allows us to plan much more efficiently. The key to this abstraction is the partitioning of the map into subgraphs of known structure with entry and exit restrictions which we can represent compactly. Planning then becomes a search in the much smaller space of subgraph configurations. Once an abstract plan is found, it can be quickly resolved into a correct (but possibly sub-optimal) concrete plan without the need for further search. We prove that this technique is sound and complete and demonstrate its practical effectiveness on a real map. A contending solution, prioritised planning, is also evaluated and shown to have similar performance albeit at the cost of completeness. The two approaches are not necessarily conflicting; we demonstrate how they can be combined into a single algorithm which outperforms either approach alone.

Characters are a critical part of storytelling and emotion is a vital part of character. Readers generally credit characters with human emotions, and it is these emotions which bring meaning to stories. To computationally construct interesting and meaningful stories we need a model of emotion which allows us to predict characters’ reactions to events in the world. There are many different psychological theories of emotion; the most popular to date for computational applications is the OCC theory. This paper describes a Discrete Event Calculus implementation of the OCC Theory of Emotion. To evaluate our system, we apply it to a selection of Aesop’s fables, and compare the output to the emotions readers expect in the same situations based on a survey.