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On line laboratory

Experiments in innovation and sustainability studies may seem difficult to realize. The usual set-ups of small scale, rigidly controlled experiments that have been successfully employed in behavioral economics, for example, don’t provide sufficient scope for interesting innovation cascades. Agent-based models do not seem at the present to offer an alternative, at least if the constraints imposed by the intentionality issue really matter. But there is an alternative that we decide to explore in INSITE: might we exploit massive multiuser online games (MMOG), in which real human beings, within the constraints imposed by the “physical laws” and interactional rules provided by the game programs, communicate with each other, act and interact – and occasionally generate emergent features that may count as innovations? Consortium member MUW has developed PARDUS, a massive multiplayer online game running since 2004, with a worldwide player base of more than 350,000 individuals.

Pardus is an open-ended game whose players live in a virtual, futuristic universe and interact with each other in a multitude of ways. Since MUW owns the game’s data base (all information is stored on log-files that must be brought into a manageable form in a database), all communication among players and all their “moves” leading up to what become identified as innovations can be tagged and analyzed – and game rules can be changed to carry out experiments on how institutional features affect innovation dynamics and sustainability. Our study of forms and types of innovation within Pardus is done in a first stage on a purely descriptive narrative basis, and second by establishing methodologies that try to quantify results. Both directions are ongoing work. The main insight so far is that it might be easiest to detect innovation through the formation of groups within the game (generative potential relationships). Groups in the game often are formed by players who pursue a special goal, aim or interest.

These goals, aims and interests (political, economical, altruistic) can be innovative and can have an impact on the whole of society. We therefore decided to devote much interest on the issue of group formation in the game. The possibilities to invent new products in Pardus is limited and does not occur at a rate that would be sufficient to go beyond a case study – type of analysis. Thus we decided to aim at the possibility to detect innovation events by understanding the formation of groups with special and innovative purposes. The data requirements and related problems are non-trivial and form a large part of the total work so far.

As a next set of problems, we identified and quantified interactions between players. We succeeded to extract 6 important types of interactions between players in the game: communication, establishing friendships, trade, revenge, establishing enemy relations, and directed aggressive/destructive behavior. These data is now all available in our database. In several occasions in the game it was possible to observe instances of innovations that players performed. For example buildings that are intended in the game to serve as factories were used in completely different ways then intended by the game designers (emergence of new attributions) Other occasions, where innovative (and adaptive to innovations) behavior is directly observable is due to new elements that are placed in the game. The game designers keep an informal ‘wish-list’ in which players can place ideas of what they would like to be able which results in a somewhat changed environment for the players. It can then be immediately observed how people adapt to these ‘innovations’.

Technologies and techniques

On the technological side we have begun to work on the following issues

  • Establishment of database: we have got an independent server where we store the data extracted in a usable form from the raw data of the log files. The server is running and can in principle be accessed through a web interface. We intend to open the data access to collaborators and scientists interested after signing an appropriate non-disclosure document.
  • Maintenance and continuous update of database: To keep up with new developments in the game the continuously generated raw log files have to be filtered and imported in the database on a regular basis. This process has to be started manually up to now.
  • Data extraction via matlab: Data for analysis has to be transferred to the matlab program. Corresponding scripts and the connection to the database have been written and installed.
  • Creating data analysis tools: We are in the continuous process to create analysis programs to extract meaningful information and knowledge from the data. The result of this is reflected in our scientific publications related to the project.
  • Measuring social interactions: We have and are extracting interaction networks of players on various levels for further analysis. This is working fine and is also reflected in the publications.
  • Monitoring group formation: We are monitoring the formation, interaction and desegregation of groups within the game. We see the groups as the main source for endogenous innovation within the game. We have begun to write analysis tools and started the quantification process.