Jeremy Gow
Imperial College London
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Jeremy Gow.
european conference on applications of evolutionary computation | 2013
Michael Cook; Simon Colton; Azalea Raad; Jeremy Gow
We introduce Mechanic Miner, an evolutionary system for discovering simple two-state game mechanics for puzzle platform games. We demonstrate how a reflection-driven generation technique can use a simulation of gameplay to select good mechanics, and how the simulation-driven process can be inverted to produce challenging levels specific to a generated mechanic. We give examples of levels and mechanics generated by the system, summarise a small pilot study conducted with example levels and mechanics, and point to further applications of the technique, including applications to automated game design.
european conference on applications of evolutionary computation | 2012
Michael Cook; Simon Colton; Jeremy Gow
We present initial results from ACCME, A Co-operative Co-evolutionary Metroidvania Engine, which uses co-operative co-evolution to automatically evolve simple platform games. We describe the system in detail and justify the use of co-operative co-evolution. We then address two fundamental questions about the use of this method in automated game design, both in terms of its ability to maximise fitness functions, and whether our choice of fitness function produces scores which correlate with player preference in the resulting games.
IEEE Transactions on Computational Intelligence and Ai in Games | 2012
Jeremy Gow; Paul A. Cairns; Simon Colton; Paul Miller
Computational analysis of player style has significant potential for video game design: it can provide insights into player behavior, as well as the means to dynamically adapt a game to each individuals style of play. To realize this potential, computational methods need to go beyond considerations of challenge and ability and account for aesthetic aspects of player style. We describe here a semiautomatic unsupervised learning approach to modeling player style using multiclass linear discriminant analysis (LDA). We argue that this approach is widely applicable for modeling player style in a wide range of games, including commercial applications, and illustrate it with two case studies: the first for a novel arcade game called Snakeotron, and the second for Rogue Trooper, a modern commercial third-person shooter video game.
computer games | 2010
Jeremy Gow; Paul A. Cairns; Simon Colton; Paul Miller; Queens Gate; York Yo; Osney Mead
Player experience is at the heart of good game design, but designers typically have limited experience data to work with. Detailed and fine-grained accounts of gaming experience would be of great value to designers and researchers alike, but recording such data is a significant challenge. We describe an approach based on post-game player commentaries, retrospective verbal reports cued by video of the gaming session and a word list. A pilot study was carried out to capture player experience of a tutorial level for a third person shooter game. We show how the technique can be used to provide useful game design feedback.
human factors in computing systems | 2010
Eduardo H. Calvillo Gámez; Paul A. Cairns; Jeremy Gow; Jonathan Back; Eddie Capstick
The workshop aims to help researchers share experience and expertise on the use of video games as research instruments in HCI and related disciplines. It will focus on existing uses, methodologies, results and issues with using video games, and is expected to lead to a better shared understanding of their current and future use across a variety of disciplines.
Entertainment Computing | 2011
Eduardo H. Calvillo Gámez; Jeremy Gow; Paul A. Cairns
There is no denying the tremendous success of video games. This makes them fascinating objects of study in their own right. But in addition, it is clear that the rich variety of worlds they offer, makes them useful for research purposes as well. This is not a new idea. They have been used in research at least since the mid 90’s, when Kirsh and Maglio [1] used Tetris to investigate the difference in the actions humans perform from a cognitive perspective. However, it seemed to us that recently games were being used more and more as new tools with which to carefully study people. For this reason, we ran a workshop at the ACM CHI 2009 [2] conference to explore the use of video games as research instruments. The conclusions reached in the workshop were that: video games motivate participants in a controlled experiment setting, but that there is a need for caution in the data collection and consideration of ethical issues. Following on from its success, we have brought together this special issue of Entertainment Computing to represent the state of the art in using video games to further wider research, rather than as a domain in themselves. This issue reflects some of the huge variety of ways in which games can help contribute to knowledge, as well as the challenges and opportunities that games offer. For this reason, we decided to accept two types of papers: research reports and technical notes. The former showcase how video games, and video game technology, are currently being used to study phenomena from different disciplines; the latter share expertise on how to use video games as tools. The most straightforward applications for video games in research is to study the players and the factors that influence their experiences. In this issue, McMahan et al. look at the effect of the naturalness of the interaction on how players performs. They use Mario Kart Wii as the game but their focus of attention is on comparisons between interaction techniques. Downs and Sundar (this issue) are looking at the psychological phenomena of people associating themselves with success and dissociating themselves from failure, and whether video games provoke similar responses as those found in social situations. Kivikangas et al. present a technical note to showcase how to collect different kinds of data, from physiological responses to qualitative data from surveys, while using videogames. Lankes and Bernhaupt (both this issue) look at people’s responses in game to facial expressions but primarily as a way of investigating people’s responses to other people, offering rich experimental stimuli that are not possible in more traditional psychological experiments. Lankes and Bernhaupt are looking at people’s interpretation of complex social scenarios. This study could have applications for the definition of avatar behaviours in video games. Away from studying the players themselves, the papers here show the opportunities for research in a wide variety of domains. Schofield (this issue) discusses the possibilities offered by using video games as a way of providing evidence in courtrooms. Staiano
IEEE Transactions on Computational Intelligence and Ai in Games | 2017
Michael Cook; Simon Colton; Jeremy Gow
Automatically generating content for videogames has long been a staple of game development and the focus of much successful research. Such forays into content generation usually concern themselves with producing a specific game component, such as a level design. This has proven a rich and challenging area of research, but in focusing on creating separate parts of a larger game, we miss out on the most challenging and interesting aspects of game development. By expanding our scope to the automated design of entire games, we can investigate the relationship between the different creative tasks undertaken in game development, tackle the higher level creative challenges of game design, and ultimately build systems capable of much greater novelty, surprise, and quality in their output. This paper, the first in a series of two, describes two case studies in automating game design, proposing cooperative coevolution as a useful technique to use within systems that automate this process. We show how this technique allows essentially separate content generators to produce content that complements each other. We also describe systems that have used this to design games with subtle emergent effects. After introducing the technique and its technical basis in this paper, in the second paper in the series we discuss higher level issues in automated game design, such as potential overlap with computational creativity and the issue of evaluation.
annual symposium on computer-human interaction in play | 2017
Christian Guckelsberger; Christoph Salge; Jeremy Gow; Paul A. Cairns
A key challenge of procedural content generation (PCG) is to evoke a certain player experience (PX), when we have no direct control over the content which gives rise to that experience. We argue that neither the rigorous methods to assess PX in HCI, nor specialised methods in PCG are sufficient, because they rely on a human in the loop. We propose to address this shortcoming by means of computational models of intrinsic motivation and AI game-playing agents. We hypothesise that our approach could be used to automatically predict PX across games and content types without relying on a human player or designer. We conduct an exploratory study in level generation based on empowerment, a specific model of intrinsic motivation. Based on a thematic analysis, we find that empowerment can be used to create levels with qualitatively different PX. We relate the identified experiences to established theories of PX in HCI and game design, and discuss next steps.
Cognitive Computation | 2016
Maria Teresa Llano; Simon Colton; Rose Hepworth; Jeremy Gow
AbstractThe invention of fictional ideas (ideation) is often a central process in the creative production of artefacts such as poems, music and paintings, but has barely been studied in the computational creativity community.n We present here a general approach to automated fictional ideation that works by manipulating facts specified in knowledge bases. More specifically, we specify a number of constructions which, by altering and combining facts from a knowledge base, result in the generation of fictions. Moreover, we present an instantiation of these constructions through the use of ConceptNet, a database of common sense knowledge. In order to evaluate the success of these constructions, we present a curation analysis that calculates the proportion of ideas which pass a typicality judgement. We further evaluate the output of this approach through a crowd-sourcing experiment in which participants were asked to rank ideas. We found a positive correlation between the participant’s rankings and a chaining inference technique that automatically assesses the value of the fictions generated through our approach. We believe that these results show that this approach constitutes a firm basis for automated fictional ideation with evaluative capacity.
human factors in computing systems | 2017
Sebastian Deterding; Jonathan Hook; Rebecca Fiebrink; Marco Gillies; Jeremy Gow; Memo Akten; Gillian Smith; Antonios Liapis; Kate Compton
Enabled by artificial intelligence techniques, we are witnessing the rise of a new paradigm of computational creativity support: mixed-initiative creative interfaces put human and computer in a tight interactive loop where each suggests, produces, evaluates, modifies, and selects creative outputs in response to the other. This paradigm could broaden and amplify creative capacity for all, but has so far remained mostly confined to artificial intelligence for game content generation, and faces many unsolved interaction design challenges. This workshop therefore convenes CHI and game researchers to advance mixed-initiative approaches to creativity support.