Noor Shaker

Noor Shaker
Aalborg University · Department of Architecture, Design and Media Technology

About

43
Publications
23,932
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
1,569
Citations

Publications

Publications (43)
Chapter
Evaluating your content generator is a very important task, but difficult to do well. Creating a game content generator in general is much easier than creating a good game content generator—but what is a “good” content generator? That depends very much on what you are trying to create and why. This chapter discusses the importance and the challenge...
Chapter
Grammars are fundamental structures in computer science that also have many applications in procedural content generation. This chapter starts by describing a classic type of grammar, the L-system, and its application to generating plants of various types. It then describes how rules and axioms for L-systems can be created through search-based meth...
Chapter
Algorithms can generate game content, but so can humans. And while PCG algorithms can generate some kinds of game content remarkably well and extremely quickly, some other types (and aspects) of game content are still best made by humans. Can we combine the advantages of procedural generation and human creation somehow? This chapter discusses mixed...
Chapter
Most games include some form of terrain or landscape (other than a flat floor) and this chapter is about how to effectively create the ground you (or the characters in your game) are standing on. It starts by describing several fast but effective stochastic methods for terrain generation, including the classic and widely used diamond-square and Per...
Chapter
Search-based procedural content generation is the use of evolutionary computation and similar methods to generate game content. This chapter gives an overview of this approach to PCG, and lists a number of core considerations for developing a search-based PCG solution. In particular, we discuss how to best represent content so that the content spac...
Chapter
Ultimately, content is generated for the player. But so far, our algorithms have not taken specific players into account. Creating computational models of a player’s behaviour, preferences, or skills is called player modelling. With a model of the player, we can create algorithms that create content specifically tailored to that player. The experie...
Chapter
Full-text available
This chapter addresses a specific type of game content, the dungeon, and a number of commonly used methods for generating such content. These methods are all “constructive”, meaning that they run in fixed (usually short) time, and do not evaluate their output in order to re-generate it. Most of these methods are also relatively simple to implement....
Book
This book presents the most up-to-date coverage of procedural content generation (PCG) for games, specifically the procedural generation of levels, landscapes, items, rules, quests, or other types of content. Each chapter explains an algorithm type or domain, including fractal methods, grammar-based methods, search-based and evolutionary methods, c...
Chapter
This chapter introduces the field of procedural content generation (PCG), as well as the book. We start by defining key terms, such as game content and procedural generation. We then give examples of games that use PCG, outline desirable properties, and provide a taxonomy of different types of PCG. Applications of and approaches to PCG can be descr...
Conference Paper
Full-text available
Player modeling and estimation of player experience have become very active research fields within affective computing, human computer interaction, and game artificial intelligence in recent years. For advancing our knowledge and understanding on player experience this paper introduces the Platformer Experience Dataset (PED) — the first open-access...
Conference Paper
This paper introduces a novel approach for pairwise preference learning through a combination of an evolutionary method and random forest. Grammatical evolution is used to describe the structure of the trees in the Random Forest (RF) and to handle the process of evolution. Evolved random forests are evaluated based on their efficiency in predicting...
Conference Paper
PCG approaches are commonly categorised as constructive, generate-and-test or search-based. Each of these approaches has itsdistinctive advantages and drawbacks. In this paper, we propose an approach to Content Generation (CG) – in particular level generation – that combines the advantages of constructive and search-based approaches thus providing...
Conference Paper
Spelunky is a game that combines characteristics from 2D platform and rogue-like genres. In this paper, we propose an evolutionary search-based approach for the automatic generation of levels for such games. A genetic algorithm is used to generate new levels according to aesthetic and design requirements. A graph is used as a genetic representation...
Conference Paper
This paper introduces an authoring tool for physics-based puzzle games that supports game designers through providing visual feedback about the space of interactions. The underlying algorithm accounts for the type and physical properties of the different game components. An area of influence, which identifies the possible space of interaction, is i...
Conference Paper
Full-text available
Evaluation is an open problem in procedural content generation research. The �eld is now in a state where there is a glut of content generators, each serving di�erent purposes and using a variety of techniques. It is di�cult to understand, quantitatively or qualitatively, what makes one generator di�erent from another in terms of its output. To rem...
Article
Full-text available
We argue for the use of active learning methods for player modelling. In active learning, the learning algorithm chooses where to sample the search space so as to optimise learning progress. We hypothesise that player modelling based on active learning could result in vastly more efficient learning, but will require big changes in how data is colle...
Article
Full-text available
Estimating affective and cognitive states in conditions of rich human-computer interaction, such as in games, is a field of growing academic and commercial interest. Entertainment and serious games can benefit from recent advances in the field as, having access to predictors of the current state of the player (or learner) can provide useful informa...
Article
Full-text available
We discuss what it means for a non-player character (NPC) to be believable or human-like, and how we can accurately assess believability. We argue that participatory observation, where the human assessing believabil-ity takes part in the game, is prone to distortion effects. For many games, a fairer (or at least complementary) assessment might be m...
Article
What are the aesthetics of platform games and what makes a platform level engaging, challenging, and/or frustrating? We attempt to answer such questions through mining a large set of crowdsourced gameplay data of a clone of the classic platform game Super Mario Bros (SMB). The data consist of 40 short game levels that differ along six key level des...
Article
We give a brief overview of the Mario AI Championship, a series of competitions based on an open source clone of the seminal platform game Super Mario Bros. The competition has four tracks. The Gameplay and Learning tracks resemble traditional reinforcement learning competitions, the Level-Generation track focuses on the generation of entertaining...
Conference Paper
In this paper we present a method for the automatic generation of content for the physics-based puzzle game Cut The Rope. An evolutionary game generator is implemented which evolves the design of levels based on a context-free grammar. We present various measures for analyzing the expressivity of the generator and visualizing the space of content c...
Conference Paper
The Turing Test Track of the Mario AI Championship focused on developing human-like controllers for a clone of the popular game Super Mario Bros. Competitors participated by submitting AI agents that imitate human playing style. This paper presents the rules of the competition, the software used, the voting interface, the scoring procedure, the sub...
Article
In this paper, we describe a methodology for capturing player experience while interacting with a game and we present a data-driven approach for modeling this interaction. We believe the best way to adapt games to a specific player is to use quantitative models of player experience derived from the in-game interaction. Therefore, we rely on crowd-s...
Article
In order to automatically generate high-quality game levels, one needs to be able to automatically verify that the levels are playable. The simulation-based approach to playability testing uses an artificial agent to play through the level, but building such an agent is not always an easy task and such an agent is not always readily available. We d...
Article
We present a demonstration of Ropossum, an authoring tool for the generation and testing of levels of the physics-based game, Cut the Rope. Ropossum integrates many features: (1) automatic design of complete solvable content, (2) incorporation of designer's input through the creation of complete or partial designs, (3) automatic check for playabili...
Article
Full-text available
The issue of discriminating among players’ styles and associating them with player profile characteristics, demographics and specific interests and needs is of vital importance for creating content, fine tuned and optimized in such a way that user engagement and interest are maximized. This paper attempts to address the issue of clustering players’...
Conference Paper
Full-text available
This paper presents the use of design grammars to evolve playable 2D platform levels through grammatical evolution (GE). Representing levels using design grammars allows simple encoding of important level design constraints, and allows remarkably compact descriptions of large spaces of levels. The expressive range of the GE-based level generator is...
Conference Paper
Full-text available
In this work, we explore the relation between expressive head movement and user profile information in game play settings. Facial gesture analysis cues are statistically correlated with players' demographic characteristics in two different settings, during game-play and at events of special interest (when the player loses during game play). Experim...
Conference Paper
Full-text available
Generating immersive game content is one of the ultimate goals for a game designer. This goal can be achieved by realizing the fact that players' perception of the same game differ according to a number of factors including: players' personality, playing styles, expertise and culture background. While one player might find the game immersive, other...
Conference Paper
Full-text available
A recent trend within computational intelligence and games research is to investigate how to affect video game players' in-game experience by de-signing and/or modifying aspects of game content. Analysing the relationship between game content, player behaviour and self-reported affective states consti-tutes an important step towards understanding g...
Article
Full-text available
The Level Generation Competition, part of the IEEE Computational Intelligence Society (CIS)-sponsored 2010 Mario AI Championship, was to our knowledge the world's first procedural content generation competition. Competitors participated by submitting level generators - software that generates new levels for a version of Super Mario Bros tailored to...
Article
Full-text available
Adapting game content to a particular player's needs and expertise constitutes an important aspect in game design. Most research in this direction has focused on adapting game difficulty to keep the player engaged in the game. Dynamic difficulty adjustment, however, focuses on one aspect of the gameplay experience by adjusting the content to increa...
Article
We describe and compare several methods for generating game character controllers that mimic the playing style of a particular human player, or of a population of human players, across video game levels. Similarity in playing style is measured through an evaluation framework, that compares the play trace of one or several human players with the pun...
Conference Paper
Full-text available
One promising avenue towards increasing player entertainment for individual game players is to tailor player experience in real-time via automatic game content generation. Modeling the relationship between game content and player preferences or affective states is an important step towards this type of game personalization. In this paper we analyse...
Article
Full-text available
The Level Generation Competition, part of the IEEE CIS-sponsored 2010 Mario AI Championship, was to our knowledge the world's first procedural content generation competition. Competitors participated by submitting level generators — software that generates new levels for a version of Super Mario Bros tailored to individual players' playing style. T...
Conference Paper
Full-text available
Recognizing players' affective state while playing video games has been the focus of many recent research studies. In this paper we describe the process that has been followed to build a corpus based on game events and recorded video sessions from human players while playing Super Mario Bros. We present different types of information that have been...
Conference Paper
Full-text available
In this paper, we show that personalized levels can be automatically generated for platform games. We build on previous work, where models were derived that predicted player experience based on features of level design and on playing styles. These models are constructed using preference learning, based on questionnaires administered to players afte...
Conference Paper
The 2010 Mario AI Championship, the successor to the 2009 Mario AI Competition, will run in association with several major international conferences focusing on computational intelligence and games. The competition will consist of three tracks: Gameplay, Learning and Level Generation, with partly overlapping organizers.
Conference Paper
Full-text available
This paper introduces SSML for using with Arabic language. SSML is part of a larger set of markup specifications for voice browsers developed through the open processes of the W3C. The essential role of the markup language is to give authors of synthesizable content a standard way to control aspects of speech output such as pronunciation, volume, p...
Conference Paper
Full-text available
In this work, we describe an approach for human finger motion and gesture detection using two cameras. The target of pointing on a flat monitor or screen is identified using image processing and line intersection. This is accomplished by processing above and side images of the hand. The system is able to track the finger movement without building t...