Software Agents for Coalition Forces

1. Software Agents for Coalition Forces Second International Conference on Knowledge Systems for Coalition Operations, 23rd and 24th April 2002 Toulouse, France By Zakaria Maamar, Paul Labbé, and Wathiq Mansoor. Presented by Paul Labbé, P. Eng., IEEE SeniorDefense R & D Canadapaulmail@ieee.org Tel.: +1 (418) 844-4000 x 4479 KSCO April 2002 Toulouse France This presentation reflects the views of the authors and does not necessarily represent the plans and policies of the Canadian Department of National Defence or of Zayed University

2. Abstract The distributed, heterogeneity, and dynamic nature of the coalition context has raised the need for new advanced technologies. These technologies aim at managing the coalition informational infrastructure, in terms of autonomy, adaptability, and scalability. To achieve this support, Software Agents (SAs) seem to be a promising approach. To develop this approach, different aspects of a coalition has to be identified. These aspects include the coalition structure; the roles and responsibilities held by people within the coalition; the flow of information within the coalition; the capabilities required or available within the coalition; and the context in which the coalition operates. For many of these aspects, SAs can be used; . For instance, the coalition structure can be associated with several SAs of different types and with different roles.

3. Introduction The ultimate objective of Allied Warfare is to increase the overall Joint/Coalition Force mission and task success rate and geopolitical influence agreed by the driving Nations. This objective imposes more difficult to meet requirements for demanding operations as in littoral warfare theater. The generation of the necessary conditions to increase the speed and accuracy of Joint/Coalition command and control include but are not limited to the material of this presentation. Allied warfare objective

4. Requirement Specification The Force Over the Horizon Track Coordinator (FOTC) data base resulted in many large inaccuracies and inconsistencies in the Global Command and Control System- Maritime (GCCS-M) picture (identity attribute of tracks (ID) jumping and time lateness) Operators believed picture to be accurate Stale data used to make decisions (Blue Force was successfully ambushed by Orange ships) FOTC held correct ID on several Hostile Tracks while LINK 11 reported them as Unknown for long periods Orange ships came within weapons range of high value blue units (Kittyhawk) without being reported for long periods of time Sanitization rules within Radiant Mercury strip vital data (e.g. source data) From live coalition exercises

5. Agent-based architecture How to deal with interoperability issues?

6. Three dimensions of interoperability issues:physical interconnectivity, application integration, and command collaboration

7. Meeting infrastructure Information exchange control Multi-agent environment Security of execution and sharing Shared decision-making ….. We propose a software agent architecture and structure to resolve some of these issues!

8. Agent-based architecture A software agent definition • An autonomous entity having the abilities to assist users when performing their operations, to collaborate with each other to jointly solve different problems, and to answer users' needs

9. Agent-based architecture A simplified CCIS model • A structure and a set of functions and tasks

10. Agent-based architecture Architecture for interoperable CCISs • Aspects to be dealt with • Maintain the autonomy and independence of the CCISs • Reduce the informational disparities of the interconnected CCISs • Protect the interconnected CCISs from the unauthorized accesses • Evaluate the communication channels performance, particularly in low-bandwidth situations (QoS, CSNI) • Help users satisfy their needs without worrying about the characteristics of the CCISs

11. Agent-based architecture

12. Agent-based architecture Architecture main characteristics • Interface-Agent • CCIS-Agent/Function-Agent • Resolution-Agent • Control-Agent • Supervisor-Agent • Advertisment infrastructure

13. It assists users in formulating needs, maps needs into requests, forwards requests to the CCIS-Agent in order to be processed, and provides users with answers obtained from the CCIS-Agent. Agent-based architecture Interface-Agent

14. Agent-based architecture CCIS-Agent • It processes user requests received from the Interface-Agent, but only if these requests require the involvement of the CCIS of this particular CCIS-Agent. In the proposed architecture, a CCIS-Agent has the ability to advertise its services by posting notes on the Bulletin Board of the Advertisement Infrastructure. To do so, the CCIS-Agent can either send a remote request to the Supervisor-Agent or can migrate to this infrastructure; the choice is based on the network status. In both cases, i.e., remote request or soft-mobility, a security level associated with the CCIS-Agent is used to identify the services this CCIS-Agent is authorized to advertise.

15. Agent-based architecture Turning CCISs into agents of MAS • Purpose: making a CCIS to behave like a SA • Build a SA on top of the CCIS

16. CCIS-Agent and Function-Agent modules

17. Agent-based architecture Resolution-Agent

18. Agent-based architecture Control-Agent

19. Agent-based architecture Supervisor-Agent

20. Agent-based architecture Advertisement Infrastructure • In an interoperating environment, CCISs are generally spread across networks and rely on low capacity and unreliable channels for communication. Moreover, a military user may use his Combat Net Radio to send and request information or may rely on mobile devices, such as portable computers, that are only intermittently connected to networks. In the proposed architecture, to avoid overloading the network, CCIS-Agents and Resolution-Agents migrate to the Advertisement Infrastructure in which CCIS-Agents advertise their services by posting notes on the Bulletin Board, whereas Resolution-Agents consult the Bulletin Board to identify the CCISs that are required to satisfy user needs.

21. Agent-based architecture Advertisement Infrastructure

22. Agent-based architecture In actions Help

23. Agent-based architecture Satisfying a user

24. What information is to be managed, and what are the properties of this information? Identify and categorize information items Specify source, destination, size, update period, comm paths, security Under what circumstances will the information be used and managed? Define: Context = Goal  Stable Conditions  Dynamic Conditions Specify the Importance (I) of each Context What a priori assessments can be made about the value of the different types of information in specific circumstances? Potential (P): relevance of information for a Context Quality (Q): how accurate information should be for a Context Timeliness (T): how recent information should be for a Context Improving Information Sharing Preliminaryanalysis

25. Improving Information Sharing Prioritization rule set OBJECTIVE: Optimize use of system resources (e.g., BW), and ensure most valuable information is processed first Priority(i,) = w I· ( wP Pi+ wQ Qi+ wT Ti+ X ) i = information item = contextI = Importance of w, wP, wQ, wT = weighting factors Pi = Potential of i for Qi  = Quality of i for Ti  = Timeliness of i for X = accounts for other factors (e.g., dynamic conditions) X = f ( Qi , qi , Ti , i) For example: qi = measured quality of ii = actual timeliness of i

26. OBJECTIVE: Assess the information attributes found in Coalition databases with the aim of integrating different data sources Maintain separate track position and ID quality measures Account for intrinsic sensor limitations (e.g., range, environmental conditions) --> the best sensor does not always have the best data Provide a systematic and consistent statistical definition of error Allow degradation in position quality during DR Problem: For security reasons, information is often sanitized or partially stripped (e.g., source) before dissemination, making quality assessment difficult Improving Information Sharing Quality assignment rule set

27. Impact of changes on mission model-based measures

28. Cost of time to discover, deliberate/fuse Value of the information presented to a commander in hypothetical OTH –T for the surface hostile contacts reported. This axis can be interpreted as a combination of positional inaccuracies of surface hostile contacts reported. 1 time to discovery cost This axis shows the age or delay since sensor time of surface hostile contacts reported after processing and deliberation.

29. Discovery/fusion gain (recipe) 2 gain from discovery 1 time to discovery cost

30. Gain in applying recipe to updates 2 gain from discovery 1 time to discovery cost 3 gain with updates

31. Loss in sharing the result 2 gain from discovery 4 cost for sharing 1 time to discovery cost 3 gain with updates

32. Sharing recipe preserve gain + capacity 5 improvement by sharing recipe instead of fusion results 2 gain from discovery 4 cost for sharing 1 time to discovery cost 3 gain with updates

33. Must be able to measure value of local discovery or fusion. When a discovery or fusion improves own picture above the received picture by a given threshold display this result locally send own data used in recipe send recipe with list of ingredients (track# used) responsible for sending own data for this recipe until found inadequate locally or remotely. Eliminate data incest and does not require the sharing of source identity (avoid loss of information required for appropriate MSDF) but provide an improved confidence in shared information. Provide “track pedigree”. First steps in developing agreed information quality schemes. Important unit and force effectiveness gain for various missions. Improving interoperability + sharing

34. Cost of time to discover, deliberate/fuse Value of the information presented to a commander in hypothetical OTH –T for the surface hostile contacts reported. This axis can be interpreted as a combination of positional inaccuracies of surface hostile contacts reported. 1 time to discovery cost This axis shows the age or delay since sensor time of surface hostile contacts reported after processing and deliberation.

35. Discovery/fusion gain (recipe) 2 gain from discovery 1 time to discovery cost

36. Gain in applying recipe to updates 2 gain from discovery 1 time to discovery cost 3 gain with updates

37. Loss in sharing the result 2 gain from discovery 4 cost for sharing 1 time to discovery cost 3 gain with updates

38. Sharing recipe preserve gain + capacity 5 improvement by sharing recipe instead of fusion results 2 gain from discovery 4 cost for sharing 1 time to discovery cost 3 gain with updates

39. Must be able to measure value of local discovery or fusion. When a discovery or fusion improves own picture above the received picture by a given threshold display this result locally send own data used in recipe send recipe with list of ingredients (track# used) responsible for sending own data for this recipe until found inadequate locally or remotely. Eliminate data incest and does not require the sharing of source identity (avoid loss of information required for appropriate MSDF) but provide an improved confidence in shared information. Provide “track pedigree”. First steps in developing agreed information quality schemes. Important unit and force effectiveness gain for various missions. Improving interoperability + sharing

40. Conclusionsand recommendations • The impact on mission effectiveness of adopting a meeting infrastructure exploiting agent-based architectures for CCISs need to be considered and be accurately assessed. • Presentedmajor characteristics of the MAS interoperability approach and the design of collaborative environments for distributed and heterogeneous CCISs. • Eight types of SAs exist in the architecture proposed for coalition support (Interface-Agent, CCIS-Agent, Resolution-Agent, Control-Agent, Function-Agent, Supervisor-Agent, Help-Agent, Route-Agent) while four stages describe this architecture operating (Initialization, Advertisement, Operation, Maintenance). • Further works need to be done for demonstrating the value of the coalition embedded characteristics of the proposed infrastructure.

41. Using information value for optimizing end users’ shared awareness is not simple but the potential gains outweigh the effort required, by delivering increases in mission precision and success rate that guarantee long term benefits and would increase public support. An agent-based architecture would also provide cost effective capabilities for future improvements, measurability, maintainability and support for training and simulation. Conclusions and recommendations (cont’d)