Environmental information querying can be cumbersome and time-consuming as users sometimes need to go through multiple Web pages for finding answers to specific questions. As a prototype modeling a multi-agent Virtual Environmental Organization (VEO), EnviroPlanner is developed to allow users to retrieve and deduce environmental information via problem-oriented question answering. In this thesis, we focus on the design and implementation of the EnviroPlanner VEO model that is supported by rule and ontology knowledge. This formalized knowledge allows EnviroPlanner's semi-automated agents to assist human experts in environmental question answering. We realized EnviroPlanner for distributed querying in the Rule Responder framework that consists of three kinds of agents: External Agent (EA), Organizational Agent (OA), and Personal Agents (PAs). The EA is the single point of entry that allows users to pose queries to the system, employing a Web interface coupled to an HTTP port to which requests are sent. EnviroPlanner consists of an extension and an instantiation of the Rule Responder framework similar in the communication architecture to the SymposiumPlanner-2011/2012 instantiations but in a very different knowledge domain. The SymposiumPlanner systems since 2011 have used two Sub-Organizational Agents (Sub-OAs) for question answering. We extended the framework to provide architectural flexibility to developers so they can add as many Sub-OAs as needed, e.g. for answering user queries about different locations or regions. The architecture designed for environmental query answering has been implemented and the EnviroPlanner prototype has been evaluated with respect to efficiency and overall performance. In addition, the EnviroPlanner prototype has been deployed on the official Rule Responder website.
Zircon - This is a contributing Drupal Theme Design by WeebPal.
