52,999 research outputs found
Underdogs and superheroes: Designing for new players in public space
We are exploring methods for participatory and public involvement of new 'players' in the design space. Underdogs & Superheroes involves a game-based methodology â a series of creative activities or games â in order to engage people experientially, creatively, and personally throughout the design process. We have found that games help engage usersâ imaginations by representing reality without limiting expectations to what's possible here and now; engaging experiential and personal perspectives (the 'whole' person); and opening the creative process to hands-on user participation through low/no-tech materials and a widely-understood approach. The methods are currently being applied in the project Underdogs & Superheroes, which aims to evolve technological interventions for personal and community presence in local public spaces
AI Researchers, Video Games Are Your Friends!
If you are an artificial intelligence researcher, you should look to video
games as ideal testbeds for the work you do. If you are a video game developer,
you should look to AI for the technology that makes completely new types of
games possible. This chapter lays out the case for both of these propositions.
It asks the question "what can video games do for AI", and discusses how in
particular general video game playing is the ideal testbed for artificial
general intelligence research. It then asks the question "what can AI do for
video games", and lays out a vision for what video games might look like if we
had significantly more advanced AI at our disposal. The chapter is based on my
keynote at IJCCI 2015, and is written in an attempt to be accessible to a broad
audience.Comment: in Studies in Computational Intelligence Studies in Computational
Intelligence, Volume 669 2017. Springe
The Challenge of Believability in Video Games: Definitions, Agents Models and Imitation Learning
In this paper, we address the problem of creating believable agents (virtual
characters) in video games. We consider only one meaning of believability,
``giving the feeling of being controlled by a player'', and outline the problem
of its evaluation. We present several models for agents in games which can
produce believable behaviours, both from industry and research. For high level
of believability, learning and especially imitation learning seems to be the
way to go. We make a quick overview of different approaches to make video
games' agents learn from players. To conclude we propose a two-step method to
develop new models for believable agents. First we must find the criteria for
believability for our application and define an evaluation method. Then the
model and the learning algorithm can be designed
Interactive Narrative for Adaptive Educational Games: Architecture and an Application to Character Education
This thesis presents AEINS, Adaptive Educational Interactive Narrative System, that supports teaching ethics for 8-12 year old children. AEINS is designed based on Keller's and Gagné's learning theories. The idea is centered around involving students in moral dilemmas (called teaching moments) within which the Socratic Method is used as the teaching pedagogy. The important unique aspect of AEINS is that it exhibits the presence of four features shown to individually increase effectiveness of edugames environments, yet not integrated together in past research: a student model, a dynamic generated narrative, scripted branched narrative and evolving non-player characters. The student model aims to provide adaptation. The dynamic generated narrative forms a continuous story that glues the scripted teaching moments together. The evolving agents increase the realism and believability of the environment and perform a recognized pedagogical role by helping in supplying the educational process.
AEINS has been evaluated intrinsically and empirically according to the following themes: architecture and implementation, social aspects, and educational achievements. The intrinsic evaluation checked the implicit goals embodied by the design aspects and made a value judgment about these goals. In the empirical evaluation, twenty participants were assigned to use AEINS over a number of games. The evaluation showed positive results as the participants appreciated the social characteristics of the system as they were able to recognize the genuine social aspects and the realism represented in the game. Finally, the evaluation showed indications for developing new lines of thinking for some participants to the extent that some of them were ready to carry the experience forward to the real world. However, the evaluation also suggested possible improvements, such as the use of 3D interface and free text natural language
Innovative integrated architecture for educational games: Challenges and merits
Interactive Narrative in game environments acts as the main catalyst to provide a motivating learning experience. In previous work, we have described how the use of a dual narrative generation technique could help to resolve the conflict between allowing high player student agency and also the track of the learning process. In this paper, we define a novel architecture that assists the dual narrative generation technique to be employed effectively in an adaptive educational game environment. The architecture composes components that individually have shown effectiveness in educational games environments. These components are graph structured narrative, dynamically generated narrative, evolving agents and a student model. An adaptive educational game, AEINS, has been developed to investigate the synergy of the architecture components. AEINS aims to foster character education at 8-12 year old children through the use of various interactive moral dilemmas that attempt the different student\u27s cognitive levels. AEINS was evaluated through a study involved 20 participants who interacted with AEINS on an individual basis
Generating Levels That Teach Mechanics
The automatic generation of game tutorials is a challenging AI problem. While
it is possible to generate annotations and instructions that explain to the
player how the game is played, this paper focuses on generating a gameplay
experience that introduces the player to a game mechanic. It evolves small
levels for the Mario AI Framework that can only be beaten by an agent that
knows how to perform specific actions in the game. It uses variations of a
perfect A* agent that are limited in various ways, such as not being able to
jump high or see enemies, to test how failing to do certain actions can stop
the player from beating the level.Comment: 8 pages, 7 figures, PCG Workshop at FDG 2018, 9th International
Workshop on Procedural Content Generation (PCG2018
Procedural content generation in gaming via evolutionary algorithms
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceThe aim of this thesis is to investigate the possibility of creating content using the Genetic Algorithms.
To this end a simple system of interconnected algorithms were developed using concepts from Role
Playing Games, specifically Dungeons and Dragons to create game content as characters, quests, and
encounters.
To be able to produce context, subsystems of map, character, quest, and encounter generators were
created. These systems or engines not only define the game space to be populated, but they also
provide each other input to create maps, quests, locations, animals, and events that are sensible and
coherent.
Randomness of the generation was essential as such a variety of noise maps and random number
generation were added to every engine in the system. Layered or singular noise maps allowed for
logical assumptions to be made, like seeing camels in a location with no rain and high temperatures.
With the base truth coming from a random noise map such as danger, civilisation, faction etc., each
system built on top of each other can get more complex.
There are several Genetic Algorithms with custom operators within the system. These algorithms take
their inputs and individuals from the respective engines and tie them all to each other through their
physical coordinates in the gaming space. The most impactful part of these algorithms is the Fitness
Functions defined with concepts from literature or CGI.
The proposed system can populate a game space with elements of desired attributes given the
constraints. The output produced consists of coherently tied story beats with some attributes already
set. Even in this simple level, this can allow not only game designers but anyone who wants to build
any kind of fictional work
Tabletop Roleplaying Games as Procedural Content Generators
Tabletop roleplaying games (TTRPGs) and procedural content generators can
both be understood as systems of rules for producing content. In this paper, we
argue that TTRPG design can usefully be viewed as procedural content generator
design. We present several case studies linking key concepts from PCG research
-- including possibility spaces, expressive range analysis, and generative
pipelines -- to key concepts in TTRPG design. We then discuss the implications
of these relationships and suggest directions for future work uniting research
in TTRPGs and PCG.Comment: 9 pages, 2 figures, FDG Workshop on Procedural Content Generation
202
Player agency in interactive narrative: audience, actor & author
The question motivating this review paper is, how can
computer-based interactive narrative be used as a constructivist learn-
ing activity? The paper proposes that player agency can be used to
link interactive narrative to learner agency in constructivist theory,
and to classify approaches to interactive narrative. The traditional
question driving research in interactive narrative is, âhow can an in-
teractive narrative deal with a high degree of player agency, while
maintaining a coherent and well-formed narrative?â This question
derives from an Aristotelian approach to interactive narrative that,
as the question shows, is inherently antagonistic to player agency.
Within this approach, player agency must be restricted and manip-
ulated to maintain the narrative. Two alternative approaches based
on Brechtâs Epic Theatre and Boalâs Theatre of the Oppressed are
reviewed. If a Boalian approach to interactive narrative is taken the
conflict between narrative and player agency dissolves. The question
that emerges from this approach is quite different from the traditional
question above, and presents a more useful approach to applying in-
teractive narrative as a constructivist learning activity
Virtual Reality Games for Motor Rehabilitation
This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any productâs acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion
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