ORCID Profile
0000-0003-4133-7913
Current Organisation
RMIT University
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Computer Gaming and Animation | Simulation And Modelling | Film, Television and Digital Media | Artificial Intelligence and Image Processing | Screen and Media Culture | Other Artificial Intelligence | Virtual Reality And Related Simulation | Pattern Recognition and Data Mining | Interactive Media | Computer-Human Interaction
ANZSRC Socio-Economic Objective (SEO)
Application tools and system utilities | Application packages | Computer software and services not elsewhere classified | Media Services not elsewhere classified | Computer Gaming Software | Behaviour and Health | The Media | Arts and Leisure not elsewhere classified | Global climate change adaptation measures | Expanding Knowledge in Technology |
Related Links
Publications
Social simulation for analysis, interaction, training and community awareness
Publisher: IEEE
Date: 12-2015
The Design and Implementation of SAMIR
Publisher: No publisher found
Date: 2005
Brain-Computer Integration: A Framework for the Design of Brain-Computer Interfaces from an Integrations Perspective
Publisher: Association for Computing Machinery (ACM)
Date: 25-09-2023
DOI: 10.1145/3603621
Abstract: Brain-computer interface (BCI) systems hold the potential to foster human flourishing and self-actualization. However, we believe contemporary BCI system design approaches unnecessarily limit these potentialities as they are approached from a traditional interaction perspective, producing command-response experiences. This article proposes to go beyond “interaction” and toward a paradigm of human-computer integration. The potential of this paradigm is demonstrated through three prototypes: Inter-Dream, a system that integrates with the brain's autonomic physiological processes to drive users toward healthy sleep states Neo-Noumena, a system that integrates with the user's affective neurophysiology to augment the interpersonal communication of emotion and PsiNet, a system that integrates interpersonal brain activity to lify human connection. Studies of these prototypes demonstrate the benefits of the integration paradigm in realizing the multifaceted benefits of BCI systems, and this work presents the brain-computer integration framework to help guide designers of future BCI integrations.
Telepathic Play: Towards Playful Experiences Based on Brain-to-brain Interfacing
Publisher: ACM
Date: 15-10-2021
Applying norms and preferences for designing flexible game rules
Publisher: Inderscience Publishers
Date: 2015
Virtual subdivision for GPU based collision detection of deformable objects using a uniform grid
Publisher: Springer Science and Business Media LLC
Date: 14-04-2012
Learning Options From Demonstrations: A <italic>Pac-Man</italic> Case Study
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2018
Narrative improvisation: Simulating game master choices
Publisher: Springer International Publishing
Date: 2018
Mel frequency cepstral coefficient temporal feature integration for classifying squeak and rattle noise
Publisher: Acoustical Society of America (ASA)
Date: 07-2021
DOI: 10.1121/10.0005201
Abstract: Fault identification using the emitted mechanical noise is becoming an attractive field of research in a variety of industries. It is essential to rank acoustic feature integration functions on their efficiency to classify different types of sound for conducting a fault diagnosis. The Mel frequency cepstral coefficient (MFCC) method was used to obtain various acoustic feature sets in the current study. MFCCs represent the audio signal power spectrum and capture the timbral information of sounds. The objective of this study is to introduce a method for the selection of statistical indicators to integrate the MFCC feature sets. Two purpose-built audio datasets for squeak and rattle were created for the study. Data were collected experimentally to investigate the feature sets of 256 recordings from 8 different rattle classes and 144 recordings from 12 different squeak classes. The support vector machine method was used to evaluate the classifier accuracy with in idual feature sets. The outcome of this study shows the best performing statistical feature sets for the squeak and rattle audio datasets. The method discussed in this pilot study is to be adapted to the development of a vehicle faulty sound recognition algorithm.
Neo-Noumena: Augmenting Emotion Communication
Publisher: ACM
Date: 21-04-2020
Enhancing theme park experiences through adaptive cyber-physical play
Publisher: IEEE
Date: 08-2015
An adaptive octree grid for GPU-based collision detection of deformable objects
Publisher: Springer Science and Business Media LLC
Date: 10-05-2014
A methodological approach for designing and evaluating intelligent applications for digital collections
Publisher: Informa UK Limited
Date: 09-2003
DOI: 10.1080/713827257
Exploring Apprenticeship Learning for Player Modelling in Interactive Narratives
Publisher: ACM
Date: 17-10-2019
Using BDI to model players behaviour in an interactive fiction game
Publisher: Springer International Publishing
Date: 2016
A dual-layer clustering scheme for real-time identification of plagiarized massive multiplayer games (MMG) assets
Publisher: IEEE
Date: 06-2010
Evoking empathy with visually impaired people through an augmented reality embodiment experience
Publisher: IEEE
Date: 03-2023
Evaluating micro-guidance sonification methods in manual tasks for Blind and Visually Impaired people
Publisher: ACM
Date: 29-11-2022
Deriving Subgoals Autonomously to Accelerate Learning in Sparse Reward Domains
Publisher: Association for the Advancement of Artificial Intelligence (AAAI)
Date: 17-07-2019
DOI: 10.1609/AAAI.V33I01.3301881
Abstract: Sparse reward games, such as the infamous Montezuma’s Revenge, pose a significant challenge for Reinforcement Learning (RL) agents. Hierarchical RL, which promotes efficient exploration via subgoals, has shown promise in these games. However, existing agents rely either on human domain knowledge or slow autonomous methods to derive suitable subgoals. In this work, we describe a new, autonomous approach for deriving subgoals from raw pixels that is more efficient than competing methods. We propose a novel intrinsic reward scheme for exploiting the derived subgoals, applying it to three Atari games with sparse rewards. Our agent’s performance is comparable to that of state-of-the-art methods, demonstrating the usefulness of the subgoals found.
XR towards tele-guidance: mixing realities in assistive technologies for blind and visually impaired people
Publisher: IEEE
Date: 03-2023
Learning Options for an MDP from Demonstrations
Publisher: Springer International Publishing
Date: 2015
An agent that learns to support users of a Web site
Publisher: Elsevier BV
Date: 02-2004
Monte Carlo tree search based algorithms for dynamic difficulty adjustment
Publisher: IEEE
Date: 08-2017
Neuroevolution of content layout in the PCG: Angry bots video game
Publisher: IEEE
Date: 06-2013
Fanky: A Tool for Animating Faces of 3D Agents
Publisher: No publisher found
Date: 2001
Integrating Skills and Simulation to Solve Complex Navigation Tasks in Infinite Mario
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2018
Measuring player skill using dynamic difficulty adjustment
Publisher: ACM
Date: 29-01-2018
Replicability and Transparency for the Creation of Public Human User Video Game Datasets
Publisher: IEEE
Date: 03-2023
Creating Adaptive and Individual Personalities in Many Characters Without Hand-Crafting Behaviors
Publisher: No publisher found
Date: 2006
DOI: 10.1007/11821830\_29
Creating Adaptive and Individual Personalities in Many Characters Without Hand-Crafting Behaviors
Publisher: Springer Berlin Heidelberg
Date: 2006
DOI: 10.1007/11821830_29
SIGHInt: Special Interest Group for Human-Computer Integration
Publisher: ACM
Date: 08-05-2021
Fanky: A Tool for Animating Faces of 3D Agents
Publisher: Springer Berlin Heidelberg
Date: 2001
Utilising reinforcement learning to develop strategies for driving auditory neural implants
Publisher: IOP Publishing
Date: 19-07-2016
DOI: 10.1088/1741-2560/13/4/046027
Abstract: In this paper we propose a novel application of reinforcement learning to the area of auditory neural stimulation. We aim to develop a simulation environment which is based off real neurological responses to auditory and electrical stimulation in the cochlear nucleus (CN) and inferior colliculus (IC) of an animal model. Using this simulator we implement closed loop reinforcement learning algorithms to determine which methods are most effective at learning effective acoustic neural stimulation strategies. By recording a comprehensive set of acoustic frequency presentations and neural responses from a set of animals we created a large database of neural responses to acoustic stimulation. Extensive electrical stimulation in the CN and the recording of neural responses in the IC provides a mapping of how the auditory system responds to electrical stimuli. The combined dataset is used as the foundation for the simulator, which is used to implement and test learning algorithms. Reinforcement learning, utilising a modified n-Armed Bandit solution, is implemented to demonstrate the model's function. We show the ability to effectively learn stimulation patterns which mimic the cochlea's ability to covert acoustic frequencies to neural activity. Time taken to learn effective replication using neural stimulation takes less than 20 min under continuous testing. These results show the utility of reinforcement learning in the field of neural stimulation. These results can be coupled with existing sound processing technologies to develop new auditory prosthetics that are adaptable to the recipients current auditory pathway. The same process can theoretically be abstracted to other sensory and motor systems to develop similar electrical replication of neural signals.
SAMIR: Your 3D Virtual Bookseller
Publisher: Springer Berlin Heidelberg
Date: 2003
Modelling Interactive Non-Linear Stories
Publisher: Springer Berlin Heidelberg
Date: 2008
Reinforcement learning to control a commander for capture the flag
Publisher: IEEE
Date: 08-2014
A BDI game master agent for computer role-playing games
Publisher: Association for Computing Machinery (ACM)
Date: 03-2017
DOI: 10.1145/2629700
Abstract: In this paper we describe an approach for developing an intelligent game master (GM) for computer role-playing games. The role of the GM is to set up the game environment, manage the narrative ow and enforce the game rules whilst keeping the players engaged. Our approach is to use the popular Belief-Desire-Intention (BDI) model of agents to developing a GM. We describe the process for creating such a GM and how we implemented a prototype of it for a scenario in the Neverwinter Nights (NWN) game. We describe the evaluation of our prototype with human participants who played the chosen NWN scenario both with and without the BDI GM. The comparison survey completed by the participants shows that the system with the BDI GM was the clear winner with respect to game replayability, flexibility, objective setting and overall interest thus, validating our hypothesis that a BDI GM will provide game players with a better gaming experience.
Fast sorting for exact OIT of complex scenes
Publisher: Springer Science and Business Media LLC
Date: 28-05-2014
The Design and Implementation of SAMIR
Publisher: Springer Berlin Heidelberg
Date: 2005
DOI: 10.1007/11552451_105
A Framework for the Development of Personalized Agents
Publisher: Springer Berlin Heidelberg
Date: 2003
Combining Monte Carlo tree search and apprenticeship learning for capture the flag
Publisher: IEEE
Date: 08-2015
Towards understanding the design of positive pre-sleep through a neurofeedback artistic experience
Publisher: ACM
Date: 02-05-2019
A survey of procedural terrain generation techniques using evolutionary algorithms
Publisher: IEEE
Date: 06-2012
Modelling Bending Behaviour in Cloth Simulation Using Hysteresis
Publisher: Wiley
Date: 22-08-2013
DOI: 10.1111/CGF.12196
Player-computer interaction features for designing digital play experiences across six degrees of water contact
Publisher: ACM
Date: 05-10-2015
Learning Options for an MDP from Demonstrations
Publisher: No publisher found
Date: 2015
Flexible story generation with norms and preferences in computer role playing games
Publisher: IEEE
Date: 08-2015
Oracle-SAGE: Planning Ahead in Graph-Based Deep Reinforcement Learning
Publisher: Springer Nature Switzerland
Date: 2023
An improved approach to reinforcement learning in Computer Go
Publisher: IEEE
Date: 08-2015
Cooking in the Dark: Exploring Spatial Audio as MR Assistive Technology for the Visually Impaired
Publisher: Springer International Publishing
Date: 2021
Using BDI to Model Players Behaviour in an Interactive Fiction Game
Publisher: No publisher found
Date: 2016
Real-Time Navigation in Classical Platform Games via Skill Reuse
Publisher: International Joint Conferences on Artificial Intelligence Organization
Date: 08-2017
Abstract: In platform videogames, players are frequently tasked with solving medium-term navigation problems in order to gather items or powerups. Artificial agents must generally obtain some form of direct experience before they can solve such tasks. Experience is gained either through training runs, or by exploiting knowledge of the game's physics to generate detailed simulations. Human players, on the other hand, seem to look ahead in high-level, abstract steps. Motivated by human play, we introduce an approach that leverages not only abstract "skills", but also knowledge of what those skills can and cannot achieve. We apply this approach to Infinite Mario, where despite facing randomly generated, maze-like levels, our agent is capable of deriving complex plans in real-time, without relying on perfect knowledge of the game's physics.
Video game personalisation techniques: A comprehensive survey
Publisher: Elsevier BV
Date: 12-2014
Narrative Improvisation: Simulating Game Master Choices
Publisher: No publisher found
Date: 2018
Backwards Memory Allocation and Improved OIT
Publisher: The Eurographics Association
Date: 2013
Informing a BDI player model for an interactive narrative
Publisher: ACM
Date: 23-10-2018
Integrated Approach to Personalized Procedural Map Generation Using Evolutionary Algorithms
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2015
A Case for Personalized Non-Player Character Companion Design
Publisher: Informa UK Limited
Date: 06-03-2023
Reducing Perceived Waiting Time in Theme Park Queues via an Augmented Reality Game
Publisher: Association for Computing Machinery (ACM)
Date: 22-01-2020
DOI: 10.1145/3361524
Abstract: Theme parks visits can be very playful events for families, however, waiting in the ride’s queues can often be the cause of great frustration. We developed a novel augmented reality game to be played in the theme park’s queue, and an in-the-wild study with X participants using log data and interviews demonstrated that every minute playing was perceived to the same extent of about 5 minutes of not playing the game. We articulate a design space for researchers and strategies for game designers aiming to reduce perceived waiting time in queues. With our work, we hope to extend how we use games in everyday life to make our lives more playful.
SAMIR: Your 3D Virtual Bookseller
Publisher: No publisher found
Date: 2003
A Framework for the Development of Personalized Agents
Publisher: No publisher found
Date: 2003
Evolving patch-based terrains for use in video games
Publisher: ACM
Date: 12-07-2011
Stress visualization in geometrically complex structures using Thermoelastic Stress Analysis and Augmented Reality
Publisher: ACM
Date: 09-10-2023
Predicting player churn in destiny: A Hidden Markov models approach to predicting player departure in a major online game
Publisher: IEEE
Date: 09-2016
Learning a Super Mario controller from examples of human play
Publisher: IEEE
Date: 07-2014
Exploration in Continuous Control Tasks via Continually Parameterized Skills
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2018
An Improved Friction Model for Cloth Simulation
Publisher: The Eurographics Association
Date: 2013
Related Organisations
Related Funding Activities
Linkage Projects - Grant ID: LP0882013
Start Date: 06-2008
End Date: 05-2011
Amount: $310,000.00
Funder: Australian Research Council
View Funded ActivityDiscovery Projects - Grant ID: DP1093290
Start Date: 2010
End Date: 12-2013
Amount: $290,000.00
Funder: Australian Research Council
View Funded ActivityLinkage Projects - Grant ID: LP130100743
Start Date: 07-2013
End Date: 12-2017
Amount: $300,000.00
Funder: Australian Research Council
View Funded ActivityLinkage Projects - Grant ID: LP180100104
Start Date: 03-2020
End Date: 03-2024
Amount: $573,620.00
Funder: Australian Research Council
View Funded Activity