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An Interoperable Framework for Distributed Coalition Planning The Collaborative Planning Model

An Interoperable Framework for Distributed Coalition Planning The Collaborative Planning Model. KSCO, 15 th February 2012 Tom Klapiscak, John Ibbotson, David Mott, Dave Braines , Jitu Patel. Motivation.

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An Interoperable Framework for Distributed Coalition Planning The Collaborative Planning Model

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  1. An Interoperable Framework for Distributed Coalition PlanningThe Collaborative Planning Model KSCO, 15th February 2012 Tom Klapiscak, John Ibbotson, David Mott, Dave Braines, Jitu Patel

  2. Motivation • Effective coalition planning requires that distributedhuman teams working in specialised functional areas maintain shared understanding. • Various specialist software tools are used to support planning within planning cells. However, these distinct tools do not interoperate. • Thus, communication between teams is inefficient and lossy: • Static, hard-copy office documents must be interpreted and adapted manually. • Only the outputs of planning activity are shared; intermediate steps in the planning process (rationale, assumptions, constraints) are often omitted. • “One size fits all” tooling is not feasible.

  3. Proposed Solution • Adopt a shared, generic and machine-interpretable ontology for the representation & communication of plans and planning processes. • Develop mapping procedures to align the data models of bespoke tools with the shared ontology. • Extend the shared ontology into new conceptual domains where necessary. • The CPM was designed with this purpose in mind: • Formal specification of the semantics of planning and collaboration. • Layered design: general abstract planning concepts can be extended to cover new military domains. • Explicit encoding of the planning process.

  4. Origins of the CPM • The International Technology Alliance (ITA) Project 12: Semantic Integration and Collaborative Planning • Initiated in May 2005 • Fundamental research in network and information sciences • An alliance between the US/UK Governments and an IBM-led consortium • 5-year program extended in 2011 for a further 5 years • Task 1:Semantic integration and Interoperability (Southampton, IBM UK, RPI, DSTL, ARL) • Task 2: Plan representation for human to human communications; and for human to machine communication (IBM UK, Southampton, Klein, DSTL, ARL) • The CPM is based on: • Established AI planning research (PLANET[3], I-N-O-V-A [4]) • SME Consultation • Extensive review of military doctrine • The CPM has been the subject of two previous empirical evaluations: • In 2008 [5] and 2011 [6, 7] • Both yielded valuable insights and encouraging results

  5. CPM Transition Project • Name: CPM Interoperability Evaluation • Started: November 2011 • Partners: DSTL, NATO, NC3A • Objectives: • Define and implement an export capability for NATO TOPFAS Operational Planning Tool (OPT). • Demonstrate the representation of TOPFAS operational plans in CPM. • Demonstrate the sharing of plans between TOPFAS and country-specific planning tools.

  6. Operational Planning Tool • Provides causal, spatial, temporal and resource views of an operations design Tool for Operations Planning Functional Area Services • Suite of planning tools developed by the NC3A to support current NATO planning doctrine • Comprehensive Operations Planning Directive (COPD) [1] • Collaborative environment for plan development and knowledge capture • Existing Export facility: MS Office documents design to support commander’s briefing • Meaning is opaque to machines • Does not support interoperability between tools

  7. Initial Work • Determine suitable (possibly composite) CPM analogues for TOPFAS vocabulary • Identify areas of apparent semantic consonance/dissonance • Investigation is based on our interpretation of informal definitions of TOPFAS vocabulary • Partial coverage of TOPFAS OPT Vocabulary: • Objective • End State • Action/Task and Effect • Decisive Conditions and Lines of Operation

  8. Example Plan: OPT Visualisation We demonstrate our initial mapping procedure using a simple operations design derived from TOPFAS training material.

  9. Objective-Goal Mapping Comparison of TOPFAS Objectives and CPM Goals based on our interpretation of informal TOPFAS vocabulary definitions CPM Goal • “A statement about the world held by an agent which the agent desires to be true”[2] TOPFAS Objective • “A clearly defined and attainable goal to be achieved.” [1] • Some Similarities • “Goal to be achieved” ≈ “Desired world state” • Both associated with an owner (or commander) ultimately responsible for its attainment • Both permit decomposition into sub-objectives • In both, sub-objectives can be used in the delegation of responsibilities from superior to subordinate

  10. Objective-GoalMapping • Some Issues • No obvious CPM analogue for some attributes held by TOPFAS objectives: e.g. Acceptability, Feasibility, Suitability • Notable difference in expressed temporal attributes: • CPM permissible intervals vs. TOPFAS “end date” instant. • What is the precise meaning of ”end date”? • The mapping must ensure temporal implications of the CPM model are aligned with those of TOPFAS

  11. Example plan: CPM Visualisation

  12. Example plan: CPM Visualisation

  13. Future Work • Identify suitable CPM analogues for more TOPFAS OPT vocabulary • Validation of proposed mappings is needed • Qualitative: E.g. SME review • Quantitative: E.g. (Semi-)formal verification techniques • Demonstration of proof of concept implementation: 14th March 2012 • Demonstration of final implementation: Summer 2012

  14. References • [1] “Allied Command Operations Planning Directive COPD Interim V1.0”, 17 December 2010. • [2] Mott, D. “CPM: Visual Guide to the CPM v3”, https://www.usukitacs.com/node/1712, 2011 • [3] Gil, Y and Blythe, J. “PLANET: A Shareable and Reusable Ontology for Representing Plans”, 2000, http://citeseer.ist.psu.edu/421975.html • [4] Tate, A. “Representing Plans as a Set of Constraints – The <I-N-O-V-A> Model. In proceedings of the 3rd International Conference on Artificial Intelligence Planning Systems, 1996 • [5] Dorneich, M.C., Mott, D., Bahrami, A., Yuan, J., Smart, A. “Evaluation of Shared Representation to Support Collaborative Multilevel Planning”, Technical Report, See http://usukita.org • [6] Michael C. Dorneich, David Mott, Ali Bahrami, John A. Allen, Jitu Patel and Cheryl Giammanco “Lessons Learned from an Evaluation of a Shared Representation to Support Collaborative Planning” • [7] Dorneich, M.C., Mott, D., Bahrami, A., Patel, J., and Giammanco, C. “Evaluation of a Shared Representation to Support Collaborative, Distributed, Coalition, Multilevel Planning”, The 5th Annual Conference of the International Technology Alliance, Maryland,US, August 2011

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