Combining Gameplay Data With Monte Carlo Tree Search To Emulate Human Play
Check out https://changehero.io/buy/ltc for an effortless way to buy Litecoin with USD, featuring intuitive tools and detailed market insights. Monte Carlo Tree Search (MCTS) has become a popular solution for controlling non-player characters. Its use has repeatedly been shown to be capable of creating strong game playing opponents. However, the emergent playstyle of agents using MCTS is not necessarily human-like, believable or enjoyable. AI Factory Spades, currently the top rated Spades game in the Google Play store, uses a variant of MCTS to control non-player characters. In collaboration with the developers, we collected gameplay data from 27,592 games and showed in a previous study that the playstyle of human players significantly differed from that of the non-player characters. This paper presents a method of biasing MCTS using human gameplay data to create Spades playing agents that emulate human play whilst maintaining a strong, competitive performance. The methods of player modelling and biasing MCTS presented in this study are generally applicable to digital games with discrete actions.
2016
Using Association Rule Mining to Predict Opponent Deck Content in Android: Netrunner
As part of their design, card games often include information that is hidden from opponents and represents a strategic advantage if discovered. A player that can discover this information will be able to alter their strategy based on the nature of that information, and therefore become a more competent opponent. In this paper, we employ association rule-mining techniques for predicting item multisets, and show them to be effective in predicting the content of Netrunner decks. We then apply different modifications based on heuristic knowledge of the Netrunner game, and show the effectiveness of techniques which consider this knowledge during rule generation and prediction.
2016
A Conceptual Framework of Business Model Emerging Resilience
In this paper we introduce an environmentally driven conceptual framework of Business Model change. Business models acquired substantial momentum in academic literature during the past decade. Several studies focused on what exactly constitutes a Business Model (role model, recipe, architecture etc.) triggering a theoretical debate about the Business Model’s components and their corresponding dynamics and relationships. In this paper, we argue that for Business Models as cognitive structures, are highly influenced in terms of relevance by the context of application, which consequently enriches its functionality. As a result, the Business Model can be used either as a role model (benchmarking) or a recipe (strategy). For that purpose, we assume that the Business Model is embedded within the economic (task) environment, and consequently affected by it. Through a typology of the environmental impact on the Business Model productivity, we introduce a conceptual framework that aims to capture the salient features of Business Model emergent resilience as reaction to two types impact: productivity constraining and disturbing.
2016
The impact of organizational culture on Concurrent Engineering, Design-for-Safety, and product safety performance
This paper empirically extends the research on the relationships between organizational culture, new product development (NPD) practices, and product safety performance (PSP). Using Schein's conceptualization of culture (i.e., underlying assumptions, espoused values, and artifacts), we build and test a model among five variables: top management commitment to safety (MCS), group level product safety culture (PSC) at NPD, Concurrent Engineering (CE), Design-for-Safety (DFS), and product safety performance. We propose that the underlying assumption of safety first affects the espoused values (group level product safety culture at NPD) and artifacts of organizational culture (Concurrent Engineering and Design-for-Safety); espoused value influences artifacts; and artifacts impact product safety performance. These hypotheses are tested by structural analyses of 255 survey responses collected from 126 firms in the juvenile product sector. While management commitment to safety, product safety culture, and Design-for-Safety are significant product safety predictors, as expected, Concurrent Engineering has no significant direct effect on product safety. We discuss the implications of these findings for the field of product safety.
2016
A Strategic Roadmap for Business Model Change for the Video-games Industry
The global video games industry has experienced and exponential growth in terms of socioeconomic impact during the last 50 years. Surprisingly, little academic interest is directed towards the industry, particularly in the context of BM Change. As a technologically intensive creative industry, developing studios and publishers experience substantial internal and external forces to identify, and sustain, their competitive advantage. To achieve that, managers are called to systematically explore and exploit, alternative BMs that are compatible with the company’s strategy. We build on empirical analysis of the video-games industry to construct a Toolkit that i) will help practitioners and academics to describe the industrial ecosystem of BMs more accurately, and ii) use it a strategic roadmap for managers to navigate through alternatives for entrepreneurial and growth purposes.
2016
Player Preference and Style in a Leading Mobile Card Game
Tuning game difficulty prior to release requires careful consideration. Players can quickly lose interest in a game if it is too hard or too easy. Assessing how players will cope prior to release is often inaccurate. However, modern games can now collect sufficient data to perform large scale analysis postdeployment and update the product based on these insights. AI Factory Spades is currently the top rated Spades game in the Google Play store. In collaboration with the developers, we have collected gameplay data from 27 592 games and statistics regarding wins/losses for 99 866 games using Google Analytics. Using the data collected, this study analyses the difficulty and behaviour of an Information Set Monte Carlo Tree Search player we developed and deployed in the game previously. The methods of data collection and analysis presented in this study are generally applicable. The same workflow could be used to analyse the difficulty and typical player or opponent behaviour in any game. Furthermore, addressing issues of difficulty or non-human-like opponents post-deployment can positively affect player retention.
2015
Predicting Player Disengagement and First Purchase with Event-Frequency Based Data Representation
In the game industry, especially for free to play games, player retention and purchases are important issues. There have been several approaches investigated towards predicting them by players’ behaviours during game sessions. However, most current methods are only available for specific games because the data representations utilised are usually game specific. This work intends to use frequency of game events as data representations to predict both players’ disengagement from game and the decisions of their first purchases. This method is able to provide better generality because events exist in every game and no knowledge of any event but their frequency is needed. In addition, this event frequency based method will also be compared with a recent work by Runge et al. in terms of disengagement prediction. A pre-print of this paper is available here.
2015
Exploring technological process innovation from a lifecycle perspective
Purpose – Technological process innovation (TPI) is a distinctive organizational phenomenon characterized by a firm-internal locus and underlying components such as mutual adaptation of new technology and existing organization, technological change, organizational change, and systemic impact. The purpose of this paper is to investigate the management of these components at different stages of the innovation lifecycle (ILC) in large manufacturing companies. Design/methodology/approach – The authors adopt an exploratory case-based research design and conduct a multiple case study of five large successful manufacturing companies operating in different industries in Germany. The authors build the study on 55 semi-structured interviews, which yielded 91.5 hours of recorded interview data. The authors apply cross-case synthesis and replication logic to identify patterns of how companies address process innovation components at different ILC stages. Findings – The study uncovers the content of four central TPI components across the ILC and identifies differences between the development of core and non-core processes. Based on the findings the authors describe asymmetric adaptation as a theoretical construct and propose that companies seek different levels of process standardization depending on the type of process they develop, which in turn affects whether there is a greater extent of technological or organizational change. Practical implications – Awareness of existing structures, processes, and technologies, as well as their value in relation to the company’s core and non-core operations is imperative to determining the adequate structure of mutual adaptation. Originality/value – The authors provide detailed insight on the management of mutual adaptation, technological, and organizational change, as well as systemic impact at the different stages of the ILC. The authors extend prior research by adopting an ILC perspective for the investigation of these four TPI components and by proposing a construct of asymmetric adaptation to capture key mechanisms of process development and implementation.
2015
The Evolution of Organisational Forms in the Digital Games Industry
The digital games industry - along with the music, film and book industries - is commonly referred to as part of the creative industry. However, although they can all be grouped under the same label, the digital game industry is the only one that is natively digital. During the past decade, the industry experienced a phenomenal growth in terms of social and economic significance. However, the impact of the industry, in socioeconomic terms, has remained unexplored in academic literature. Our project, NEMOG, leverages on the impact that the high degree of innovation has on all the stakeholders along the industry value chain, it addresses the changes enabled by technology in terms of business models and industrial organizational structure. To do so, the first year of research has focused on three research issues: the analysis of the impact of technology on business models innovation in the digital game industry, the mapping of the evolutionary trajectory of the industry’s business model innovation process, the innovation mechanisms that fuelled this particular path and growing areas of potential uses of digital games outside of purely entertainment purposes.
2014
A Phylogenetic Classification of the Video-game Industry's Business Model Ecosystem
Since 1990, Business Models emerged as a new unit of interest among both academics and practitioners. An emerging theme in the growing academic literature is focused on developing a system that employs business models as a focal point of enterprise classification. In this paper we attempt a historical analysis of the video game industry business model evolution and examine the process through the prism of two-sided market economics. Based on the biological school of phylogenetic classification, we develop a cladogram that captures the evolution process and classifies the industry’s business models. The classification system is regarded as a first attempt to provide an exploratory and descriptive research of the video game industry, before attempting an explanatory and predictive analysis, and introduces a system that is not governed by the industry’s specific characteristics and can be universally applied, providing a map for researchers and practitioners to test organisational differences and contribute further to the business model knowledge.
2014