2.50
Hdl Handle:
http://hdl.handle.net/2436/34172
Title:
Online Learning From Observation For Interactive Computer Games
Authors:
Hartley, Thomas; Mehdi, Qasim; Gough, Norman
Other Titles:
Proceedings of CGAIMS’2005; Games
Abstract:
The research presented in this paper describes an architecture, which enables an agent to predict an observed entity’s actions (most likely a human’s) online. Case-based approaches have been utilised by a number of researchers for online action prediction in interactive applications. Our architecture builds on these works and provides a number of novel contributions. Specifically our architecture offers a more comprehensive state representation, behaviour prediction and a more robust case maintenance approach. The proposed architecture is fully described in terms of interactive simulations (specifically first person shooter (FPS) computer games); however it would be applicable to other interactive applications, such as intelligent tutoring and surveillance systems. We conclude the paper by evaluating our proposed architecture and discussing how the system will be implemented.
Citation:
In: Mehdi, Q., Gough, N. and Elmaghraby, A. (Eds), Proceedings of CGAIMS’2005. 6th International Conference on Computer Games: Artificial Intelligence and Mobile Systems, 27-30 July 2005, Louisville, Kentucky, USA.
Publisher:
University of Wolverhampton, School of Computing and Information Technology
Issue Date:
2005
URI:
http://hdl.handle.net/2436/34172
Additional Links:
http://www.cgames.org/; http://www.wlv.ac.uk/Default.aspx?page=14750
Type:
Meetings & Proceedings
Language:
en
ISBN:
0-9549016-1-6
Appears in Collections:
Game Simulation and Artificial Intelligence Centre (GSAI)

Full metadata record

DC FieldValue Language
dc.contributor.authorHartley, Thomas-
dc.contributor.authorMehdi, Qasim-
dc.contributor.authorGough, Norman-
dc.date.accessioned2008-08-05T11:19:16Z-
dc.date.available2008-08-05T11:19:16Z-
dc.date.issued2005-
dc.identifier.citationIn: Mehdi, Q., Gough, N. and Elmaghraby, A. (Eds), Proceedings of CGAIMS’2005. 6th International Conference on Computer Games: Artificial Intelligence and Mobile Systems, 27-30 July 2005, Louisville, Kentucky, USA.en
dc.identifier.isbn0-9549016-1-6-
dc.identifier.urihttp://hdl.handle.net/2436/34172-
dc.description.abstractThe research presented in this paper describes an architecture, which enables an agent to predict an observed entity’s actions (most likely a human’s) online. Case-based approaches have been utilised by a number of researchers for online action prediction in interactive applications. Our architecture builds on these works and provides a number of novel contributions. Specifically our architecture offers a more comprehensive state representation, behaviour prediction and a more robust case maintenance approach. The proposed architecture is fully described in terms of interactive simulations (specifically first person shooter (FPS) computer games); however it would be applicable to other interactive applications, such as intelligent tutoring and surveillance systems. We conclude the paper by evaluating our proposed architecture and discussing how the system will be implemented.en
dc.language.isoenen
dc.publisherUniversity of Wolverhampton, School of Computing and Information Technologyen
dc.relation.urlhttp://www.cgames.org/en
dc.relation.urlhttp://www.wlv.ac.uk/Default.aspx?page=14750en
dc.subjectE-learningen
dc.subjectInteractive computer gamesen
dc.subjectArchitectureen
dc.subjectOnline action predictionen
dc.subjectInteractive simulationsen
dc.subjectGames based learning-
dc.titleOnline Learning From Observation For Interactive Computer Gamesen
dc.title.alternativeProceedings of CGAIMS’2005en
dc.title.alternativeGames-
dc.typeMeetings & Proceedingsen
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