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DC Field | Value | Language |
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dc.contributor.author | Grappiolo, Corrado | - |
dc.contributor.author | Yannakakis, Georgios N. | - |
dc.date.accessioned | 2018-04-18T06:24:57Z | - |
dc.date.available | 2018-04-18T06:24:57Z | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | Grappiolo, C., & Yannakakis G. N. (2012) Towards detecting group identities in complex artificial societies. In T. Ziemke, C. Balkenius, & J. Hallam (Eds.), From Animals to Animats 12. SAB 2012. Lecture Notes in Computer Science, vol. 7426, (pp. 421-430). Springer, Berlin, Heidelberg. | en_GB |
dc.identifier.isbn | 9783642330933 | - |
dc.identifier.uri | https://www.um.edu.mt/library/oar//handle/123456789/29277 | - |
dc.description.abstract | This paper presents a framework for modelling group structures and dynamics in both artificial societies and human-populated virtual environments such as computer games. The group modelling (GM) framework proposed focuses on the detection of existing, pre-defined group structures and is composed of a reinforcement learning method that infers collaboration values from the society’s local interactions and a clustering algorithm that detects group identities based on the learned collaboration values. An empirical evaluation of the framework in the social ultimatum bargain game shows that the GM method proposed is robust independently of the size of the society and the locality of the interactions. | en_GB |
dc.description.sponsorship | This work has been supported, in part, by the FP7 ICT project SIREN (project no: 258453). | en_GB |
dc.language.iso | en | en_GB |
dc.publisher | Springer | en_GB |
dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
dc.subject | Computer games -- Group identity | en_GB |
dc.subject | Group games | en_GB |
dc.subject | Virtual reality | en_GB |
dc.title | Towards detecting group identities in complex artificial societies | en_GB |
dc.type | bookPart | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.description.reviewed | peer-reviewed | en_GB |
dc.identifier.doi | 10.1007/978-3-642-33093-3_42 | - |
Appears in Collections: | Scholarly Works - InsDG |
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Towards_detecting_group_identities_in_complex_artificial_societies_2012.pdf Restricted Access | 1.51 MB | Adobe PDF | View/Open Request a copy |
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