Enkhbold Nyamsuren

Pre-attentive and attentive vision module

This paper introduces a new vision module, called PAAV, developed for the cognitive architecture ACT-R. Unlike ACT-Rs default vision module that was originally developed for top-down perception only, PAAV was designed to model a wide range of tasks, such as visual search and scene viewing, where pre-attentive bottom-up processes are essential for the validity of a model. PAAV builds on attentive components of the default vision module and incorporates greater support for modeling pre-attentive components of human vision. The module design incorporates the best practices from existing models of vision. The validity of the module was tested on four different tasks.

Set as an Instance of a Real‐World Visual‐Cognitive Task

Complex problem solving is often an integration of perceptual processing and deliberate planning. But what balances these two processes, and how do novices differ from experts? We investigate the interplay between these two in the game of SET. This article investigates how people combine bottom-up visual processes and top-down planning to succeed in this game. Using combinatorial and mixed-effect regression analysis of eye-movement protocols and a cognitive model of a human player, we show that SET players deploy both bottom-up and top-down processes in parallel to accomplish the same task. The combination of competition and cooperation of both types of processes is a major factor of success in the game. Finally, we explore strategies players use during the game. Our findings suggest that within-trial strategy shifts can occur without the need of explicit meta-cognitive control, but rather implicitly as a result of evolving memory activations.

RAGE Architecture for Reusable Serious Gaming Technology Components

For seizing the potential of serious games, the RAGE project—funded by the Horizon-2020 Programme of the European Commission—will make available an interoperable set of advanced technology components software assets that support game studios at serious game development. This paper describes the overall software architecture and design conditions that are needed for the easy integration and reuse of such software assets in existing game platforms. Based on the component-based software engineering paradigm the RAGE architecture takes into account the portability of assets to different operating systems, different programming languages, and different game engines. It avoids dependencies on external software frameworks and minimises code that may hinder integration with game engine code. Furthermore it relies on a limited set of standard software patterns and well-established coding practices. The RAGE architecture has been successfully validated by implementing and testing basic software assets in four major programming languages C#, C++, Java, and TypeScript/JavaScript, resp.. Demonstrator implementation of asset integration with an existing game engine was created and validated. The presented RAGE architecture paves the way for large scale development and application of cross-engine reusable software assets for enhancing the quality and diversity of serious gaming.

The RAGE Software Asset Model and Metadata Model

Software assets are key output of the RAGE project and they can be used by applied game developers to enhance the pedagogical and educational value of their games. These software assets cover a broad spectrum of functionalities – from player analytics including emotion detection to intelligent adaptation and social gamification. In order to facilitate integration and interoperability, all of these assets adhere to a common model, which describes their properties through a set of metadata. In this paper the RAGE asset model and asset metadata model is presented, capturing the detail of assets and their potential usage within three distinct dimensions – technological, gaming and pedagogical. The paper highlights key issues and challenges in constructing the RAGE asset and asset metadata model and details the process and design of a flexible metadata editor that facilitates both adaptation and improvement of the asset metadata model.

The Effect of Visual Representation Style in Problem-Solving: A Perspective from Cognitive Processes

Using results from a controlled experiment and simulations based on cognitive models, we show that visual presentation style can have a significant impact on performance in a complex problem-solving task. We compared subject performances in two isomorphic, but visually different, tasks based on a card game of SET. Although subjects used the same strategy in both tasks, the difference in presentation style resulted in radically different reaction times and significant deviations in scanpath patterns in the two tasks. Results from our study indicate that low-level subconscious visual processes, such as differential acuity in peripheral vision and low-level iconic memory, can have indirect, but significant effects on decision making during a problem-solving task. We have developed two ACT-R models that employ the same basic strategy but deal with different presentations styles. Our ACT-R models confirm that changes in low-level visual processes triggered by changes in presentation style can propagate to higher-level cognitive processes. Such a domino effect can significantly affect reaction times and eye movements, without affecting the overall strategy of problem solving.

Making Serious Games with Reusable Software Components

This paper explains the RAGE project, which proposes a component-based software architecture to accommodate and amplify serious game development. The RAGE project (rageproject.eu) is a serious gaming flagship project funded by the Horizon 2020 Programme of the European Commission. Compliancy with the component-based architecture preserves the portability of software to different platforms and programming languages and its easy integration in wide variety of game engines. RAGE has developed up to 40 cutting edge reusable software components (all free, open source software) and has made these available on its market place portal at gamecomponents.eu.

Automated Adaptation and Assessment in Serious Games: A Portable Tool for Supporting Learning

We introduce the Adaptation and Assessment (TwoA) component, an open-source tool for serious games, capable of adjusting game difficulty to player skill level. Technically, TwoA is compliant with the RAGE (Horizon 2020) game component architecture, which offers seamless portability to a variety of popular game development platforms. Conceptually, TwoA uses a modified version of the Computer Adaptive Practice algorithm. Our version offers two improvements over the original algorithm. First, TwoA improves the balancing of a player’s motivation and game challenge. Second, TwoA reduces the selection bias that may arise for items of similar difficulty by adopting a fuzzy selection rule. The improvements are validated using multi-agent simulations.

Efficient Software Assets for Fostering Learning in Applied Games

Digital game technologies are a promising way to enable training providers to reach other target groups, namely those who are not interested in traditional learning technologies. Theoretically, through using digital game technologies we are able to foster the acquisition of any competence by specifying competency structures, offering adequate problem solving support while maintaining motivation and taking personality into consideration as part of the tailored game experience. In this paper, we illustrate how this is done within the RAGE project, which aims to develop, transform, and enrich advanced technologies into self-contained gaming assets for the leisure games industry to support game studios in developing applied games easier, faster, and more cost effectively. The software assets discussed here represent a modular approach for fostering learning in applied games. These assets address four main pedagogical functions: competency structures (i.e., logical order for learning), motivation, performance support (i.e., guidance to maintain learning), and adaption to the player’s personality.