Measuring player’s behaviour change over time in public goods game
An important issue in public goods game is whether player's behaviour changes over time, and if so, how significant it is. In this game players can be classified into different groups according to the level of their participation in the public good. This problem can be considered as a concept d...
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| Format: | Conference or Workshop Item |
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2016
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| Online Access: | https://eprints.nottingham.ac.uk/37670/ |
| _version_ | 1848795507968704512 |
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| author | Fattah, Polla Aickelin, Uwe Wagner, Christian |
| author_facet | Fattah, Polla Aickelin, Uwe Wagner, Christian |
| author_sort | Fattah, Polla |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | An important issue in public goods game is whether player's behaviour changes over time, and if so, how significant it is. In this game players can be classified into different groups according to the level of their participation in the public good. This problem can be considered as a concept drift problem by asking the amount of change that happens to the clusters of players over a sequence of game rounds. In this study we present a method for measuring changes in clusters with the same items over discrete time points using external clustering validation indices and area under the curve. External clustering indices were originally used to measure the difference between suggested clusters in terms of clustering algorithms and ground truth labels for items provided by experts. Instead of different cluster label comparison, we use these indices to compare between clusters of any two consecutive time points or between the first time point and the remaining time points to measure the difference between clusters through time points. In theory, any external clustering indices can be used to measure changes for any traditional (non-temporal) clustering algorithm, due to the fact that any time point alone is not carrying any temporal information. For the public goods game, our results indicate that the players are changing over time but the change is smooth and relatively constant between any two time points. |
| first_indexed | 2025-11-14T19:33:12Z |
| format | Conference or Workshop Item |
| id | nottingham-37670 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:33:12Z |
| publishDate | 2016 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-376702020-05-04T18:09:54Z https://eprints.nottingham.ac.uk/37670/ Measuring player’s behaviour change over time in public goods game Fattah, Polla Aickelin, Uwe Wagner, Christian An important issue in public goods game is whether player's behaviour changes over time, and if so, how significant it is. In this game players can be classified into different groups according to the level of their participation in the public good. This problem can be considered as a concept drift problem by asking the amount of change that happens to the clusters of players over a sequence of game rounds. In this study we present a method for measuring changes in clusters with the same items over discrete time points using external clustering validation indices and area under the curve. External clustering indices were originally used to measure the difference between suggested clusters in terms of clustering algorithms and ground truth labels for items provided by experts. Instead of different cluster label comparison, we use these indices to compare between clusters of any two consecutive time points or between the first time point and the remaining time points to measure the difference between clusters through time points. In theory, any external clustering indices can be used to measure changes for any traditional (non-temporal) clustering algorithm, due to the fact that any time point alone is not carrying any temporal information. For the public goods game, our results indicate that the players are changing over time but the change is smooth and relatively constant between any two time points. 2016-09-23 Conference or Workshop Item PeerReviewed Fattah, Polla, Aickelin, Uwe and Wagner, Christian (2016) Measuring player’s behaviour change over time in public goods game. In: SAI Intelligent Systems Conference 2016, 20-22 Sep 2016, London, UK. clustering; external cluster validity; measuring change over time; temporal data https://arxiv.org/pdf/1609.02672v1.pdf |
| spellingShingle | clustering; external cluster validity; measuring change over time; temporal data Fattah, Polla Aickelin, Uwe Wagner, Christian Measuring player’s behaviour change over time in public goods game |
| title | Measuring player’s behaviour change over time in public goods game |
| title_full | Measuring player’s behaviour change over time in public goods game |
| title_fullStr | Measuring player’s behaviour change over time in public goods game |
| title_full_unstemmed | Measuring player’s behaviour change over time in public goods game |
| title_short | Measuring player’s behaviour change over time in public goods game |
| title_sort | measuring player’s behaviour change over time in public goods game |
| topic | clustering; external cluster validity; measuring change over time; temporal data |
| url | https://eprints.nottingham.ac.uk/37670/ https://eprints.nottingham.ac.uk/37670/ |