Applying KAoS Services to Ensure Policy Compliance for Semantic Web Services Workflow Composition and Enactment

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.In this paper we describe our experience in applying KAoS services to ensure policy compliance for Semantic Web Services workflow composition and enactment. We are developing these capabilities within the context of two applications: Coalition Search and Rescue (CoSAR-TS) and Semantic Firewall (SFW). We describe how this work has uncovered requirements for increasing the expressivity of policy beyond what can be done with description logic (e.g., role-value-maps), and how we are extending our representation and reasoning mechanisms in a carefully controlled manner to that end. Since KAoS employs OWL for policy representation, it fits naturally with the use of OWL-S workflow descriptions generated by the AIAI I-X planning system in the CoSARTS application. The advanced reasoning mechanisms of KAoS are based on the JTP inference engine and enable the analysis of classes and instances of processes from a policy perspective. As the result of analysis, KAoS concludes whether a particular workflow step is allowed by policy and whether the performance of this step would incur additional policy-generated obligations. Issues in the representation of processes within OWL-S are described. Besides what is done during workflow composition, aspects of policy compliance can be checked at runtime when a workflow is enacted. We illustrate these capabilities through two application examples. Finally, we outline plans for future work

Coalition Search and Rescue - Task Support: Intelligent Task Achieving Agents on the Semantic Web

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.The Coalition Search and Rescue Task Support (CoSAR-TS) has been a DARPA DAML Program project to provide advanced capabilities linking models of organizational structures, policies, and doctrines with intelligent task support software. The project integrates AIAI’s I-X planning and collaboration technology, IHMC’s KAoS policy and domain services, and Semantic Web Services of various kinds. Search and rescue operations by nature require the kind of rapid dynamic composition of available policy-constrained services making it a good use case for Semantic Web technologies. Other participants in the application include BBN Technologies, SPAWAR, AFRL, and Carnegie Mellon University. At the beginning of the project, the joint AIAI/IHMC aims were: - Development of base technologies respectively I-X/I-Plan and KAoS Policy and Domain Services, - Deployment of the technology in a realistic CoAX agents demonstrator scenario, - Persuasion of closer integration of these two technologies with a perspective of a uniform tool release in the future. These goals were achieved in the subsequent years of the project as follows: - Year 1: Distributed multi-agent systems were developed and integrated with the semantic web in a realistic coalition search and rescue scenario. This culminated in an AAAI-2004 Intelligent Systems Demonstrator for CoSAR-TS. - Year 2: An initial web services composition and policy analysis tool for semantic web services (I-K-C) was implemented. The activity culminated in an IEEE Intelligent Systems journal article and an ISWC 2004 conference paper. Results of the project are available from several web sites including: the CoSAR-TS Project web site, the DAML-program results related SemWebCentral web site, and the I-K-C project web pages at AIAI and IHMC (please see Appendix C for details). The software developed during the project is available for download from the above-mentioned web pages. The projected also produced an impressive list of quality publications that thoroughly documented and publicized the project results in the research and military communities. The technology developed by the project is being used in a further transition effort with JFCOM/JPRA in the Co-OPR project, a seedling for DARPA’s Integrated Battle Command program (http://www.aiai.ed.ac.uk/project/co-opr/)

KAoS Policy Management for Semantic Web Services

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.Despite rapid advances in Web Services, the user community as demanding requirements continue to outstrip available technology solutions. To help close this gap, Semantic Web Services advocates are defining and implementing many new and significant capabilities (www.swsi.org). These new capabilities should more fully harness Web Services' power through explicit representations of Web resources' underlying semantics and the development of an intelligent Web infrastructure that can fully exploit them. Semantic Web languages, such as OWL, extend RDF to let users specify ontologies comprising taxonomies of classes and inference rules. Both people and software agents can effectively use Semantic Web Services. Agents will increasingly use the combination of semantic markup languages and Semantic Web Services to understand and autonomously manipulate Web content in significant ways. Agents will discover, communicate, and cooperate with other agents and services and - as we'll describe - will rely on policy-based management and control mechanisms to ensure respect for human-imposed constraints on agent interaction. Policy-based controls of Semantic Web Services can also help govern interaction with traditional (nonagent) clients. In the mid 1990s, we began to define the initial version of KAoS, a set of platform-independent services that let people define policies ensuring adequate predictability and controllability of both agents and traditional distributed systems. With various research partners, we' re also developing and evaluating a generic model of human-agent teamwork that includes policies to assure natural and effective interaction in mixed teams of people and agents - both software and robotic. We're exploiting the power of Semantic Web representations to address some of the challenges currently limiting Semantic Web Services' widespread deployment

Managing semantic Grid metadata in S-OGSA

Grid resources such as data, services, and equipment, are increasingly being annotated with descriptive metadata that facilitates their discovery and their use in the context of Virtual Organizations (VO). Making such growing body of metadata explicit and available to Grid services is key to the success of the VO paradigm. In this paper we present a model and management architecture for Semantic Bindings, i.e., firstclass Grid entities that encapsulate metadata on the Grid and make it available through predictable access patterns. The model is at the core of the S-OGSA reference architecture for the Semantic Grid

Policy Management across Multiple Platforms and Application Domains

One of the challenges of building a policy management framework is making it flexible enough to handle differences in both policy semantics and enforcement strategies across multiple platforms and application domains. The system must be expressive enough in each application domain to provide the richness needed for interesting policies. It must also provide a simple and flexible enforcement mechanism for adaptation to a variety of systems. In this paper we discuss the application of the KAoS policy services framework to human-robot teamwork—an application that involves a variety of application domains and enforcement at different levels of control; from low level network resource control to high level organizational constraints and coordination management. The study culminated in an outdoor field exercise that required coordination of mixed sub teams composed of two people and five robots whose task was to find and apprehend an intruder on a Navy pier. 1

Policy and Contract Management for Semantic Web Services

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.This paper summarizes our efforts to develop capabilities for policy and contract management for Semantic Web Services applications. KAoS services and tools allow for the specification, management, analyzes, disclosure and enforcement of policies represented in OWL. We discuss three current Semantic Web Services applications as examples of the kinds of roles that a policy management framework can play: as an authorization service in grid computing environments, as a distributed policy specification and enforcement capability for a semantic matchmaker, and as a verification tool for services composition and contract management

KARMEN: Multi-agent Monitoring and Notification for Complex Processes

Abstract. Early and consistent detection of abnormal conditions is important to the safe and efficient operation of complex industrial processes. Our research focuses on enabling the operators and engineers who control and maintain such systems to describe process conditions to software agents, deploy such agents to continuously monitor live process data, and receive appropriate notification from their personal agents concerning the process state. The resulting dynamic population of monitoring agents is managed by our agile computing framework according to policies that define computing and networking resource restrictions as well as user notification requirements and preferences.

Agent Systems for Coalition Search and Rescue Task Support

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.The Coalition Search and Rescue Task Support project shows cooperative agents supporting a highly dynamic mission in which AI task planning, inter-agent collaboration, workflow enactment, policy-managed services, semantic web queries, semantic web services matchmaking and knowledge-based notifications are employed

Social Order and Adaptability in Animal and Human Cultures as Analogues for Agent Communities: Toward a Policy-Based Approach

Abstract. In this paper we discuss some of the ways social order is maintained in animal and human realms, with the goal of enriching our thinking about mechanisms that might be employed in developing similar means of ordering communities of agents. We present examples from our current work in human-agent teamwork, and we speculate about some new directions this kind of research might take. Since communities also need to change over time to cope with changing circumstances, we also speculate on means that regulatory bodies can use to adapt. 1