Zoekresultaten

Integrating emergence and progression

This paper investigates how structures of emergence and progression in games might be integrated. By leveraging the formalism of Machination diagrams the shape of the mechanics and a game’s internal economy that typically control progression in games are exposed. Two strategies to create mechanics that control progression but exhibit more emergent behavior by including feedback loops are presented.

The theoretical framework of the ‘archive-as-Is’

Engineering emergence

Dit proefschrift presenteert twee theoretische kaders voor het ontwerpen van games en beschrijft hoe game designers deze kunnen inzetten om het game ontwerpproces te stroomlijnen. Er bestaan op dit moment meerdere ontwerptheorie¨en voor games, maar geen enkele kan rekenen op een breed draagvlak binnen de game industrie. Vooral academische ontwerptheorie¨en hebben regelmatig een slechte reputatie. Het eerste kader dat game designers inzicht biedt in spelregels en hun werking heet Machinations en maakt gebruik van dynamische, interactieve diagrammen. Het tweede theoretische kader van dit proefschrift, Mission/Space, richt zich op level-ontwerp en spelmechanismen die de voortgang van een speler bepalen. In tegenstelling tot bestaande modellen voor level-ontwerp, bouwt Mission/Space voort op het idee dat er in een level twee verschillende structuren bestaan. Mission-diagrammen worden gebruikt om de structuur van taken en uitdagingen voor de speler te formaliseren, terwijl space-diagrammen de ruimtelijke constructie formaliseren. Beide constructies zijn aan elkaar gerelateerd, maar zijn niet hetzelfde. De verschillende wijzen waarop missies geprojecteerd kunnen worden op een bepaalde ruimte speelt uiteindelijk een belangrijke rol in de totstandkoming van de spelervaring.

Governing roles and responsibilities in a human-machine decision-making context

Proper decision-making is one of the most important capabilities of an organization. Therefore, it is important to have a clear understanding and overview of the decisions an organization makes. A means to understanding and modeling decisions is the Decision Model and Notation (DMN) standard published by the Object Management Group in 2015. In this standard, it is possible to design and specify how a decision should be taken. However, DMN lacks elements to specify the actors that fulfil different roles in the decision-making process as well as not taking into account the autonomy of machines. In this paper, we re-address and-present our earlier work [1] that focuses on the construction of a framework that takes into account different roles in the decision-making process, and also includes the extent of the autonomy when machines are involved in the decision-making processes. Yet, we extended our previous research with more detailed discussion of the related literature, running cases, and results, which provides a grounded basis from which further research on the governance of (semi) automated decision-making can be conducted. The contributions of this paper are twofold; 1) a framework that combines both autonomy and separation of concerns aspects for decision-making in practice while 2) the proposed theory forms a grounded argument to enrich the current DMN standard.

The Decision Transparency Framework

Business decisions and business logic are an important part of an organization’s daily activities. In the not so near past they were modelled as integrative part of business processes, however, during the last years, they are managed as a separate entity. Still, decisions and underlying business logic often remain a black box. Therefore, the call for transparency increases. Current theory does not provide a measurable and quantitative way to measure transparency for business decisions. This paper extends the understanding of different views on transparency with regards to business decisions and underlying business logic and presents a framework including Key Transparency Indicators (KTI) to measure the transparency of business decisions and business logic. The framework is validated by means of an experiment using case study data. Results show that the framework and KTI’s are useful to measure transparency. Further research will focus on further refinement of the measurements as well as further validation of the current measurements.

Simulating Mechanics to Study Emergence in Games

This paper presents the latest version of the Machinations framework. This framework uses diagrams to represent the flow of tangible and abstract resources through a game. This flow represents the mechanics that make up a game’s interbal economy and has a large impact on the emergent gameplay of most simulation games, strategy games and board games. This paper shows how Machinations diagrams can be used simulate and balance games before they are built.