14,320 research outputs found
Problems in modeling the software development process as an adventure game
SESAM (Software Engineering Simulation by Animated Models) is a simulator for practicing the role of a software project manager. Its long term goal is to provide a tool for training CS students. As a research project, SESAM calls for an integrated model of the software development process, reflecting and quantifying many phenomena observed in real software projects. We are currently using the second prototype, which can already demonstrate some rational behaviour. More important, however, were our observations in the process of constructing SESAM. They shed light on the current state of software engineering, and on the applicability of metrics. SESAM is being developed in an evolutionary style by the Software Engineering Department (Lehrstuhl) at Stuttgart University; it is implemented in Smalltalk-80 on Unix-Workstations. This paper concentrates on the fundamental questions raised by the work on SESAM. A more complete description of our work has been published before
Gaming techniques and the product development process : commonalities and cross-applications
The use of computer-based tools is now firmly embedded within the product development process, providing a wide range of uses from visualisation to analysis. However, the specialisation required to make effective use of these tools has led to the compartmentalisation of expertise in design teams, resulting in communication problems between individual members. This paper therefore considers how computer gaming techniques and strategies could be used to enhance communication and group design activities throughout the product design process
Advances in Teaching & Learning Day Abstracts 2004
Proceedings of the Advances in Teaching & Learning Day Regional Conference held at The University of Texas Health Science Center at Houston in 2004
Deep learning for video game playing
In this article, we review recent Deep Learning advances in the context of
how they have been applied to play different types of video games such as
first-person shooters, arcade games, and real-time strategy games. We analyze
the unique requirements that different game genres pose to a deep learning
system and highlight important open challenges in the context of applying these
machine learning methods to video games, such as general game playing, dealing
with extremely large decision spaces and sparse rewards
Text-based Adventures of the Golovin AI Agent
The domain of text-based adventure games has been recently established as a
new challenge of creating the agent that is both able to understand natural
language, and acts intelligently in text-described environments.
In this paper, we present our approach to tackle the problem. Our agent,
named Golovin, takes advantage of the limited game domain. We use genre-related
corpora (including fantasy books and decompiled games) to create language
models suitable to this domain. Moreover, we embed mechanisms that allow us to
specify, and separately handle, important tasks as fighting opponents, managing
inventory, and navigating on the game map.
We validated usefulness of these mechanisms, measuring agent's performance on
the set of 50 interactive fiction games. Finally, we show that our agent plays
on a level comparable to the winner of the last year Text-Based Adventure AI
Competition
Expressive recommender systems through normalized nonnegative models
We introduce normalized nonnegative models (NNM) for explorative data
analysis. NNMs are partial convexifications of models from probability theory.
We demonstrate their value at the example of item recommendation. We show that
NNM-based recommender systems satisfy three criteria that all recommender
systems should ideally satisfy: high predictive power, computational
tractability, and expressive representations of users and items. Expressive
user and item representations are important in practice to succinctly summarize
the pool of customers and the pool of items. In NNMs, user representations are
expressive because each user's preference can be regarded as normalized mixture
of preferences of stereotypical users. The interpretability of item and user
representations allow us to arrange properties of items (e.g., genres of movies
or topics of documents) or users (e.g., personality traits) hierarchically
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Modeling and formal veriļ¬cation of gaming storylines
Video games are becoming more and more interactive with increasingly complex plots. These plots typically involve multiple parallel storylines that may converge and diverge based on player actions. This may lead to situations that are inconsistent or impassable. Current techniques for planning and testing game plots involve naive means such as text documents, spreadsheets, and critical path testing. Recent academic research [1] [2] [3] examines the design planning problems, but neglect testing and veriļ¬cation of the possible plot lines. These complex plots have thus until now been handled inadequately due to a lack of a formal methodology and tools to support them. In this dissertation, we describe how we develop methods to 1) characterize storylines (SChar), 2) deļ¬ne a storyline description language (SDL), and 3) create a storyline veriļ¬cation tool based in formal veriļ¬cation techniques (StoCk) that use our SDL as input. SChar (Storyline Characterization) help game developers characterize the category of story line they are working on (e.g. linear, branching and plot) through a tool that give a set of guided questions. Our SDL allows its users to describe storylines in a consistent format similar to how they reason about storylines, but in such a way that it can be used for formal veriļ¬cation. StoCk accepts storylines, described in SDL, to be formally veriļ¬ed using SPIN for errors. StoCk is also examined in three common use cases found in the gaming industry used as a tool 1) during storyline creation 2) during quality assurance and 3) during storyline implementation. The combination of SChar, SDL, and StoCk provides designers, writers, and developers a novel methodology and tools to verify consistency in large and complex game plots.Electrical and Computer Engineerin
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