Identifying Events Taking Place in Second Life Virtual Environments

Abstract

Second Life is one of the most popular multi-purpose online virtual worlds, which supports applications in diversified areas relating to real-life activities. Moreover, it is possible to use Second Life in testing Artificial Intelligence theories by creating intelligent virtual agents. For the successful implementation of many of these applications, it is important to accurately identify events taking place inside Second Life. This involves extracting low-level spatio-temporal data and identifying the embedded high-level domain-specific information. This is an aspect that has not been taken into consideration in the prior research related to Second Life. This paper presents a framework that extracts data from Second Life with high accuracy and high frequency, and identifies the high-level domain-specific events and other contextual information embedded in these low-level data. This is guided by our virtual environment formalism, which defines events and states in a virtual environment. This framework is further enhanced to be connected with multiagent development platforms, thus demonstrating its use in the area of Artificial Intelligence.