Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Jessica Rivera Villicana"'
Publikováno v:
Sensors, Vol 23, Iss 20, p 8375 (2023)
Epilepsy is a chronic neurological disorder affecting around 1% of the global population, characterized by recurrent epileptic seizures. Accurate diagnosis and treatment are crucial for reducing mortality rates. Recent advancements in machine learnin
Externí odkaz:
https://doaj.org/article/733d8f15cc8d44a5834d45e555d2b3c7
Autor:
Sheng Wong, Anj Simmons, Jessica Rivera‐Villicana, Scott Barnett, Shobi Sivathamboo, Piero Perucca, Zongyuan Ge, Patrick Kwan, Levin Kuhlmann, Rajesh Vasa, Kon Mouzakis, Terence J. O'Brien
Publikováno v:
Epilepsia Open.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fd72fa17f84925847b39f54f2839eb67
https://doi.org/10.1002/epi4.12704
https://doi.org/10.1002/epi4.12704
Publikováno v:
ESEM
Background: Meeting the growing industry demand for Data Science requires cross-disciplinary teams that can translate machine learning research into production-ready code. Software engineering teams value adherence to coding standards as an indicatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::873004ec76c9aa16541bc54fc9c335b7
http://arxiv.org/abs/2007.08978
http://arxiv.org/abs/2007.08978
Publikováno v:
CHI PLAY (Companion)
In this paper we present an early Apprenticeship Learning approach to mimic the behaviour of different players in a short adaption of the interactive fiction Anchorhead. Our motivation is the need to understand and simulate player behaviour to create
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f3e84382eb641f04f57cd32b591fd9e
https://doi.org/10.1145/3341215.3356314
https://doi.org/10.1145/3341215.3356314
Publikováno v:
Interactive Storytelling ISBN: 9783030338930
ICIDS
ICIDS
In this paper, we present a new modality for intelligent interactive narratives within the theatre domain. We discuss the possibilities of using an intelligent agent that serves as a drama manager and as an actor that plays a character within the liv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cc1e20c6499b4c5164bc7a08308082f8
https://doi.org/10.1007/978-3-030-33894-7_24
https://doi.org/10.1007/978-3-030-33894-7_24
Publikováno v:
Proceedings of the 2018 Annual Symposium on Computer-Human Interaction in Play.
This work focuses on studying players behaviour in interactive narratives with the aim to simulate their choices. Besides sub-optimal player behaviour due to limited knowledge about the environment, the difference in each player's style and preferenc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4672422cca6c5ff785a4be30e1c7ff14
https://doi.org/10.1145/3242671.3242700
https://doi.org/10.1145/3242671.3242700
Publikováno v:
Interactive Storytelling ISBN: 9783319482781
ICIDS
ICIDS
Player Modelling is one of the challenges in Interactive Narratives (INs), where a precise representation of the players mental state is needed to provide a personalised experience. However, how to represent the interaction of the player with the gam
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61ae0ff829756cb65bec14df95e57138
https://doi.org/10.1007/978-3-319-48279-8_19
https://doi.org/10.1007/978-3-319-48279-8_19
Publikováno v:
CIG
Capture the flag (CTF) is a popular game mode for many blockbuster games. Agents in these games struggle against the players who learn to adapt to their strategies leading to the players dissatisfaction. We present our work on using Reinforcement Lea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ece31a0a0869d3aadc7639c83ba8c51b
https://doi.org/10.1109/cig.2014.6932880
https://doi.org/10.1109/cig.2014.6932880
Autor:
Sheng Wong, Anj Simmons, Jessica Rivera‐Villicana, Scott Barnett, Shobi Sivathamboo, Piero Perucca, Zongyuan Ge, Patrick Kwan, Levin Kuhlmann, Rajesh Vasa, Kon Mouzakis, Terence J. O'Brien
Publikováno v:
Epilepsia Open, Vol 8, Iss 2, Pp 252-267 (2023)
Abstract Electroencephalogram (EEG) datasets from epilepsy patients have been used to develop seizure detection and prediction algorithms using machine learning (ML) techniques with the aim of implementing the learned model in a device. However, the
Externí odkaz:
https://doaj.org/article/dd221382004549ed888af5dc9dc587a0