Time Critical Strike Integration Via Intelligent Agent Technology

Transcription

1 Time Critical Strike Integration Via Intelligent Agent Technology Gerard J. Mayer, Martin O. Hofmann, Kenneth R. Whitebread, Lori A. Pridmore, Peter M. Gerken, Michael D. Orr Lockheed Martin Advanced Technology Laboratories Camden, NJ {gmayer, mhofmann, kwhitebr, lpridmor, pgerken, Abstract The demands of current and future operations point to the need to be able to rapidly and seamlessly execute the steps of Time Critical Strike (TCS). One of the biggest barriers to this requirement is the lack of interoperability among current Command and Control (C2) systems in TCS. A TCS C2 system is stood up from a diverse set of legacy and emerging systems, developing yet again as many pairwise interconnects as needed. Though disagreeable, this is often seen as the only solution. In the future, ideas such as the Joint Battlespace Infosphere concept may alleviate this situation. But in the near term, interoperable, intelligent-agent technology provides a reusable, achievable solution to this problem. Lockheed Martin Advanced Technology Laboratories (LM ATL) has developed and demonstrated this capability with funding from the Defense Advanced Research Projects Agency (DARPA) over four years in five separate Fleet Battle Experiments (FBEs). An architecture built around intelligent software agents allows the warfighting process (TCS) to be explicitly implemented using intelligent agents to provide a unified process across separate, stove-piped systems. Intelligent agents allow each system to be aware of which systems are providers of input data, triggers, and alerts, and which downstream systems require the system s outputs and when. Proxy agents turn passive constituent systems, unaware of each other, into proactive components capable of initiating and guiding computations on the user s behalf. Never again will the human user have to copy target coordinates from one system s screen and manually enter them into another. The agent-based architecture easily adapts to additions or modifications of constituent systems; i.e., this solution is reusable. Experience has shown that the effort and time to construct the agent-based solution is lower than traditional methods, even though the finished product is more general. This seeming contradiction is explained by the fact that agent solutions inherently leverage software reuse as part of constructing the agent solution. In an Air Force TCS scenario, for example, we configured an interoperability demonstration using three major Air Force C2 1

2 systems in less than two weeks using DARPA s intelligent-agent technology, which was recently demonstrated to the highest level Air Force personnel. The benefits of opting for a intelligent agent-based, system-of-systems architecture extend beyond the ease and re-usability of system interoperation. Execution of the TCS cycle can be enhanced by applying agent technology to decision support within the cycle, including plan monitoring, threat alerting, information correlation, and information dissemination. Agents augment human teams, automate tedious and time-consuming tasks, and surrogates perform faster than humans without getting tired. Agents, unlike human operators, do not get overwhelmed by the stress of rapid, parallel execution of multiple, time-critical, decision-making processes. In this paper, we review the benefits of agent-based C2 architectures to the TCS cycle and its application to modern warfare. We also present the evidence we have gathered through experiments, field exercises, and demonstrations to show the utility of agent-based C2 architectures, including significant reductions in the time to prosecute targets. Introduction Lockheed Martin Advanced Technology Laboratories, funded to develop intelligent agents since 1995 by multiple government research organizations, notably DARPA, has developed a significant capability to develop and deliver mobile, intelligent-agent applications. We have developed more than 20 applications and matured our Extendible Mobile Agent Architecture (EMAA) to Technical Readiness Level (TRL) 7. EMAA is a complete mobile-agent platform with support for agent launch, migration, and management at a patented agent dock, with distributed event messaging that is reliable even with agent mobility. Our agent applications cover many areas of interest to DoD, with several addressing capability aimed at TCS. Our primary TCS application is funded by DARPA s Control of Agent Based Systems (CoABS) program. CoABS efforts have set out to demonstrate that a decision-support capability based on interoperable, intelligent-agent technology accelerates and improves human decisions in TCS operations. LM ATL is participating in the USN FBE series, inserting the Cooperating Agents for Specific Tasks (CAST) intelligent-agent systems into the experimental, digital, fires network, which is focused on TCS. CAST has matured through five FBEs, and is at TRL 6. CAST will be used in FBE-J in July 2002 for its sixth FBE. A more detailed description of CAST in TCS operations was presented at the 2001 Fire Control Conference 1. A summary of CAST capability in these FBEs is described as follows: In FBE-D (Fall 1998), CAST was demonstrated to TCS personnel as a stand-alone system interacting with non-fbe intelligence and C2 systems. This resulted in significant operational feedback as to the primary limitations in existing TCS operations. CAST capability was significantly designed based on this operational input. 1 Martin O. Hofmann, Daria Chacón, Gerard Mayer, Kenneth R. Whitebread, James Hendler, CAST Agents: Network-Centric Fires Unleashed, 2001 Fire Control Conference Proceedings. 2

3 In FBE-E (Spring 1999), cooperating CAST agents monitored events from multiple intelligence sources. While individual pieces of information may seem insignificant, scout agents collected corroborating evidence and performed threat assessment on the correlated picture. Such an exhaustive search cannot be performed without automation, and no other automation tool but agents had the flexibility and efficiency to deal with disparate information from legacy systems. In FBE-F (Fall 1999), CAST demonstrated reach-back from Fifth Fleet in Bahrain to national resources in the continental United States. CAST used mobile agents to monitor data in an intelligence-database simulation installed at USN Space Warfare Command, San Diego. System-wide integration problems prevented CAST from playing a significant role in FBE-F. The integration problems pointed to the need for an open, standards-based integration approach like the CoABS Grid. In FBE-H (Summer 2000), CAST collected target-relevant information and images from various shipboard Command, Control, Communications, and Intelligence (C4I) systems, highlighting facts of critical importance, such as no-strike targets. CAST presented operators with a wealth of decision-ready information at the click of a button. Strike operators routinely used CAST to increase their situational awareness across the warfare grids. CAST agent technology readily provided autonomy, persistence, and efficiency to monitor dynamic information channels. CAST agents extracted information and images from relational databases, web pages, and -message streams. In FBE-I (Summer 2001), our CAST framework had matured to the point where we could in a matter of weeks configure CAST to interact with all relevant data sources on the FBE network. CAST had thus achieved its primary mission to make available, with a single click on the CAST button, all the information pertinent for rapid, effective TCS. The intelligent-agent application to the TCS has several major benefits. These are faster performance of the total TCS process; reduced operator workload for repetitive mundane tasks; virtual integration for all components of the system, whether they are new or legacy components; and the ability to dynamically connect and disconnect software components from the system Improved Time Critical Strike Cycle Time The primary operational payoff is in significantly improved TCS cycle times. CAST s agent technology tested in the FBE reduced the Find, Fix, Track, Target part of TCS from 45 to nine minutes. This can be further reduced with agents taking a more proactive role. The role of agents improving Engage and Assess parts of the TCS have also been demonstrated, where agents got the appropriate information to the operator just as soon as it was in the system. The key reasons that agents make such a dramatic improvement is that the component systems of the TCS interoperate with each other through agents and that the agents can define and implement a unified process. EMAA agents can be tasked for a variety of functions, such as searching for specific information, persistent monitoring of information or combinations of events, and intelligent dissemination of information to specific components. EMAA agents perform these, and other tasks and are mobile across software components. This effectively allows EMAA agents to 3

4 interoperate across all components of a TCS system. From the operator point of view, the agents can respond to his requests from all agent-connected components. Prior to intelligent agents participating in the TCS processes, the operators were the executers of these processes. Operators spent 90 percent of their time searching for information by their direct interaction with one or two component systems and by verbal interaction with other operators at their one or two components. All of this multi-operator activity across tens of components to perform each search is what caused the traditional TCS process to take 45 minutes or more. Now, a unified process can be described to the agents who then can search tens of components in a unified process. Not only is the agent unified process significantly more efficient, but the process is continuously repeatable. CAST agents execute according to a modular, task-oriented workflow model, which gives them persistence and autonomy. Tasks and workflow are configurable, reusable components; this minimizes time and effort to tailor CAST to new decision-support applications. CAST technology addresses security and resource management, and robustly deals with sometimes unreliable and congested military networks. Reduced Operator Workload EMAA agents can be tasked to perform most information search, comparison, transformation, and notification. These tasks represent a significant amount of the mundane tasks operators routinely perform. Operators using CAST have reported an enormous reduction in simple tasks that occupied much of their time. Information agents assigned to dynamic data sources maintained persistent watch for changes after the initial results returned. For example, agents persistently monitored the Image Product Library for new imagery that might assist in targeting before the strike or in bomb-damage assessment after the strike. CAST collected target-relevant information and images from various shipboard C4I systems, highlighting facts of critical importance, such as no-strike targets. Strike operators routinely used CAST to increase their situational awareness across the warfare grids. CAST agents extracted facility information from the Modernized Integrated Database (MIDB), and noted units and equipment located at this facility. This information influenced choice and planning of strike missions. CAST also retrieved no-strike target information from MIDB. CAST agents interacted with the web client to the Image Transformation Server to fetch images that showed the selected target location. After FBE-H, Commander Second Fleet described CAST as showing promise, replacing redundant manual manipulations. The ability of agents to repeatedly and tirelessly perform these tasks had a large impact in reducing errors in the process. Additional information, such as no-strike lists or related information on web sites or on Internet Relay Chat channels, was routinely accessed by CAST agents, and improved the overall quality of the TCS process while reducing operator workload. 4

5 Component Integration with Agents The ability of EMAA agents to connect to tens of components in a TCS system allowed the operators to search and view information that the agents discovered as if all the components were really integrated. Really integrating tens of components into a common system where components are uniquely developed by various organizations and managed by still other organizations has been elusive and costly. Even if this was achievable at a fixed point in time, new components that should be added or components that were extensively modified would need to be integrated anew. EMAA agent mobility during FBE-I proved to be another effective capability of CAST agents. Our CAST system operators found that the mobile CAST agents that retrieved Common Operating Picture (COP) tracks from the ashore server never failed, despite frequent connectivity losses of the network between the USS Coronado and the ashore systems. CAST mobile agents used a proprietary mobility service that is tolerant of low bandwidth, unreliable network links. FBE system architects frequently considered web technology as an alternative to autonomous, mobile-agent technology. In fact, agent and web technology complement each other rather than compete. Web technology leverages large, centralized servers that store all relevant information, such as the Digital Target Folders (DFTs). Commercial web technology usually assumes reliable, high-bandwidth network connections. For the foreseeable future, DoD networks do not match these expectations. For example, operators on the USS Stennis avoided using the DFTs during FBE-I, because of the time it took to load and display the folders across the wireless satellite link. Web technology performs most of the processing at the servers, which has led to server overload during heavy use. Applets provide some local processing, but are severely limited by the security sandbox model. CAST agents used web technology in several ways. CAST docks attached local web servers with servlet technology to manage interactions with users and display results on the local area network. CAST agents inserted information in the DFTs on the request of a user, where they became part of central information repositories. CAST agents retrieved information and imagery from web interfaces, where they logged in, followed hyperlinks, and filled in forms like the human user to select the relevant data. Naval Warfare Development Command (NWDC) and LM ATL have cooperated in the FBEs to develop this complementary web- and agent-computing model. The combination of centralized (web) and local (agent) processing as well as shared (web) and user-specific (agent) displays have worked well in the FBEs. Under internal research and development funding, LM ATL is preparing CAST agents to leverage the ontologies and XML markup of the next-generation, semantic web. A CoABS technology developed to support agent-based systems called the CoABS Grid is middleware that integrates heterogeneous agent, object, and legacy systems. The CoABS Grid, based on Sun s Jini network technology, supports formation of a dynamic system of systems, where components join and leave while the overall system continues to function. CAST uses the CoABS Grid, and can thus be rapidly extended to interact with additional information sources. 5

6 In FBE-I, we verified that the CoABS Grid effectively supported dynamic system integration. CAST relied on the CoABS Grid to locate and access multiple components. We have developed a small set of generic Grid wrappers for relational databases and web interfaces. We had to construct special-purpose wrappers for complex sources, such as MIDB, that required data validation and mediation. The one-time effort to create these wrappers ranged from one day (COP tracks) to three weeks (MIDB), but the effort has quickly been amortized through reuse. The integration of CAST with the XML Data Mover proved the power of the CoABS Grid model. We adapted one of our Grid wrappers in less than a day, and the XML Data Mover developers connected it to their application the next day. We were able to verify correct operation the same evening across the Internet. Through this interface, CAST agents, or any component connected to the CoABS Grid, can prompt the XML Data Mover to update specific records in the DFT from the MIDB. This example showed how simple conventions supported by a powerful infrastructure simplify open-system interconnectivity. The agent-oriented paradigm and our CAST agent platform accelerate system development for specific applications and exercises. Already, CAST multi-agent systems are much quicker to build and field than traditional, monolithic decision-support systems. However, it still takes skilled developers to adapt CAST to a specific FBE. Our goal is to develop an Interoperable Intelligent Agent Toolkit (I2AT) that will let military decision makers compose and configure CAST for their personal needs with minimal recourse to contractor support. Already, CAST agents can be composed from reusable, Java bean-like tasks and conform to one of a small number of behavior patterns. We believe that such a toolkit will be a sufficient enabler to transition agent-oriented systems into widespread use as decision-support systems. We are developing the I2AT under DARPA CoABS funding, which will overcome a major transition hurdle; it will enable domain expert users to configure and personalize intelligent, agent-based automation processes. Summary At a recent DARPA-sponsored meeting of the agent research community, RADM Robert Sprigg, NWDC, cited CAST in his keynote address for its successful application of agent technology in the FBEs. Participation in the FBE series has proven that autonomous, intelligent agents can substantially improve time-sensitive decision processes. The EMAA architecture provides the foundation for reusability and rapid, disciplined development of distributed agent applications. EMAA provides distributed resource registration and look-up, a clean separation of mobile-agent tasks, and stationary resources connected to the distributed agent docks. EMAA is a pure Java application, and has run on Sun Solaris, Microsoft Windows 98 and NT, and Linux. EMAA is the core of over 20 of our recent agent applications. Agent applications developed using EMAA do not unduly burden computational and network resources. Measurements taken during FBE-I showed that the typical size of our CAST agents 6

7 fell between five and six Kbytes. Comparison with other agent systems showed that CAST agents added the lowest overhead to the actual task code and data 2. Each agent system adds some overhead due to agent management, but EMAA came closest to the raw TCP (transmissioncontrol-protocol) transfer times. Autonomous agents distribute the computational burden among processing nodes. Mobile agents move the information processing closer to the information source, e.g., to a node on the same local area network. LM ATL s mobile-agent technology follows the applicable DoD security guidance. According to the guidance document on the use of mobile code 3, our mobile agents posed the moderate, manageable risk of Category 2 mobile Java code. EMAA contains mechanisms to sign code and establish trusted code sources that mitigate the added security risks of mobile agents. Future Directions LM ATL has demonstrated the ability to quickly connect CAST to other TCS systems for Air Force applications. On LM ATL internal funding, it took only two weeks of development to demonstrate CAST working with Integrated Space Command and Control, components of Theater Battle Management Core Systems and other components. This was demonstrated to top Air Force leaders to show horizontal integration. This is leading to awareness and interest in CAST and EMAA by other members of the TCS community. We are supporting NWDC s Expeditionary Sensor Grid initiative, providing our mobile-agent technology and our legacy system exploitation technology. For FBE-J, we plan to introduce additional decision-support capabilities into CAST to support coalition warfare. These capabilities are a synchronization of the COP and filtering and monitoring of chat channels to enable realtime information sharing by coalition partners. CAST and EMAA are working in conjunction with Radiant Mercury to provide information with multi-level security. Our technology development is focused on improving the agents ability to interpret the information they encounter as well as accelerating agent-system assembly and configuration. Our hypothesis is that agents not only revolutionize decision-support capabilities, but also the development and insertion of decision-support tools. Where contractors used to work for years to develop stove-piped systems, we are developing the I2AT, whose agent, task, and life-cycle patterns will let military users tailor agent applications for a specific deployment. 2 David Kotz, George Cybenko, Robert S. Gray, Guofei Jiang, Ronald A. Peterson, Martin O. Hofmann, Daria A. Chacón, Kenneth R. Whitebread, and James Hendler. Performance Analysis of Mobile Agents for Filtering Data Streams on Wireless Networks. Mobile Networks and Applications, 7(2), March, Assistant Secretary of Defense, Policy Guidance for Use of Mobile Code Technologies in Department of Defense (DoD) Information Systems, November 7,

8 Acknowledgements CAST applications described in this paper were funded under DARPA s CoABS contracts F C-0162 and F C We wish to acknowledge the continued support of intelligent-agent research by LCDR Dylan Schmorrow, DARPA CoABS Program Manager. Special thanks to RADM Sprigg, Commander NWDC, and to Paul Schmidle, NWDC s Information Knowledge Advantage (IKA) initiative lead, for supporting insertion of CAST into the IKA suite. We owe gratitude to each of the NWDC FBE Directors and Fires Initiative Leads for their support and insights. 8