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

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/)

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

Intelligent Agents 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 demonstration shows cooperative agents supporting a highly dynamic mission in which AI task planning, inter-agent collaboration, workflow enactment, policy-managed communications, semantic web queries, semantic web services matchmaking and knowledge-based notifications are employed

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

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

The POLIPO Security Framework

Systems of systems are dynamic coalitions of distributed, autonomous and heterogeneous systems that collaborate to achieve a common goal. While offering several advantages in terms of scalability and flexibility, the systems of systems paradigm has a significant impact on systems interoperability and on the security requirements of the collaborating systems. In this chapter we introduce POLIPO, a security framework that protects the information exchanged among the systems in a system of systems, while preserving systems’ autonomy and interoperability. Information is protected from unauthorized access and improper modification by combining context-aware access control with trust management. Autonomy and interoperability are enabled by the use of ontology-based services. More precisely, each authority may refer to different ontologies to define the semantics of the terms used in the security policy of the system it governs and to describe domain knowledge and context information. A semantic alignment technique is then employed to map concepts from different ontologies and align the systems’ vocabularies. We demonstrate the applicability of our solution with a prototype implementation of the framework for a scenario in the maritime safety and security domain