Validating Procedural Knowledge in the Open Virtual Collaboration Environment

ABSTRACT This paper describes the OpenVCE system, which is an open-source environment that integrates Web 2.0 technology and a 3D virtual world space to support collaborative work, specifically in large-scale emergency response scenarios, where the system has been evaluated. The support is achieved through procedural knowledge that is available to the system. OpenVCE supports the distributed knowledge engineering of procedural knowledge in a semi-formal framework based on a wiki. For the formal aspect it relies on a representation used in AI planning, specifically, Hierarchical Task Networks, which corresponds naturally to the way emergency response procedures are described in existing Standard Operating Procedures. Knowledge engineering is supported by domain analysis that may highlight issues with the representation. The main contribution of this paper lies in a reasonably informal description of the analysis. The procedural knowledge available to OpenVCE can be utilized in the environment through plans generated by a planner and given to the users as intelligent, distributed to-do lists. The system has been evaluated in experiments using emergency response experts, and it was shown that procedural uncertainty could be improved, despite the complex and new technologies involved. Furthermore, the support for knowledge engineering through domain analysis has been evaluated using several domains from the International Planning Competition, and it was possible to bring out some issues with these examples

Using Expressive and Flexible Action Representations to Reason about Capabilties for Intelligent Agent Cooperation

Centre for Intelligent Systems and their ApplicationsThe aim of this thesis is to adress the problem of capability brokering. A capability-brokering agent recieves capability advertisements from problem-solving agents and problem descriptions from problem-holding agents. The amin task for the broker is to find problem-solving agents that have the capabilities to address problems described to the broker by a problem-holding agent. Capability brokering poses two problems: for advertisements, and matching problems and capabilities, to find capable problem-solvers. For the representation part of the problem, there have been a number of representations in AI that address similar issues. We review various logical representations, action representations, and representations for models of problem solving and conclude that, while all of these areas have some positive features for the representation of capabilities, they also all have serious drawbacks. We describe a new capability description language, CDL, which shares the positive features of previous languages while avoiding their drawbacks. CDL is a decoupled action representation into which arbitrary state representations can be plugged, resulting in the expressiveness and flexibility needed for capability brokering. Reasoning over capability descriptions takes place on two levels. The outer level deals with agent communication and we have devloped the Knowledge Query and Manipulation Language (KQML) here. At the inner level the main task is to decide whether a capability description subsumes a problem description. In CDL thee subsumtion relation for achievable objectives is defined in terms of the logical entailment relation betwenn sentences in the state language used within CDL. The definition of subsumption for performable tasks in turn is based on this definition for achievable objectives. We describe algoritms in this thesis which have all been implemented and incorporated into he Java Agent Template where they proved sufficient to operationalise anumber of example scenarios. The two most important featues of CDL are its expressiveness and its flexibility. By expressiveness we mean the ability to express more than is possible in other representations. By flexibility we mean the possibility to delay decisions regarding the compromises that have to be made to knowledge representation time. The scenarions we ahve implemted illustrate the importance of the features and we have shown in this thesis that CDL indeed possess thease features. Thus, CDL is an expressive and flexible capability description language that can be used to address the problem of capability brokering