1. 2006 The ITSIMBW Environment for Simulation and Decision Support Philipp Hügelmeyer Dr. Timo Steffens

2. 2006 Features of ITSimBW Scalability Focus on Cummunication Freedom of modelling Viewing alternatives graphically (decisions and/or events) Basic principles of technical realization Language for Agent-based Modelling of Processes and Scenarios (LAMPS) Graph Metrics Roadmap for the next steps (Gis, HLA …) Features of ITSimBW Scalability Focus on Cummunication Freedom of modelling Viewing alternatives graphically (decisions and/or events) Basic principles of technical realization Language for Agent-based Modelling of Processes and Scenarios (LAMPS) Graph Metrics Roadmap for the next steps (Gis, HLA …) O utline

3. 2006 Global view Mission troups act as one single agent S calability S calability Multi-Scale Approach Strategic level HQ in Europe Mission A-Land SatCom Time scale 1 minute Local effects are modeled More detailed agents Time scale 1 second Tactical level

4. 2006 S calability S calability Multi-Scale Approach functionality (how detailed are functions/effects modeled/simulated ?) Scalable complexity: time(in which time steps will the simulation proceed ?) space(which spacial scale will be chosen for modeling? changable during run time at different places different changes possible system can be built in several stages (also depending on modeling efforts) Granularity in modeling should be further refined only if it makes sense

5. 2006 S calability which level of accuracy is needed? Level of accuracy Level of significance

6. 2006 Assumptions/ models Complexity Plausibility low very high Level of significance S calability which level of accuracy is needed? Level of accuracy

7. 2006 Results Correctness Usefulness very high low Level of significance S calability which level of accuracy is needed? Level of accuracy Complexity Plausibility low very high Assumptions/ models

8. 2006 high Level of significance S calability which level of accuracy is needed? Level of accuracy Results Correctness Usefulness very high low Complexity Plausibility low very high Assumptions/ models high

9. 2006 extremely high low A simulation model must be adjustable to the appropriate scope This scope is changing from task to task Level of significance S calability which level of accuracy is needed? Level of accuracy high Results Correctness Usefulness very high low Complexity Plausibility low very high Assumptions/ models high

10. 2006 Language for Agent based Modelling of Processes and Scenarios Based on high-level Petri-Nets Actions describe the effects that agents apply to themselves or to other agents Relations denote the links between places, actions, and agents. Agents correspond to the conditions of Petri nets Graphical and textual representation Not restricted to a timing model Time scaling is possible Language for Agent based Modelling of Processes and Scenarios Based on high-level Petri-Nets Actions describe the effects that agents apply to themselves or to other agents Relations denote the links between places, actions, and agents. Agents correspond to the conditions of Petri nets Graphical and textual representation Not restricted to a timing model Time scaling is possible LAMPSLAMPS

11. 2006 LAMPSLAMPS

12. Agent Autonomous active elements What are the active system components ? Persons Machines, vehicles Objects, Bridges, … Agents carry out the system processes … A gent Architecture A gent Architecture FTA

13. 2006 Agent Tag Agents cause effects by producing tags How do active elements interact ? Causing effects spoken messages physical interaction effects of weapons … A gent Architecture A gent Architecture FTA

14. 2006 Agent Tag Agents are self-responsible for their own behavior, there is no direct action from outside Taking effects reading a message realizing physical effects taking orders … A gent Architecture A gent Architecture FTA How do active elements interact ?

15. 2006 Agent Tag Tag types describe the form, tag instances contain the concrete data Tags have a type order form general message physical power (effects) … A gent Architecture A gent Architecture FTA How do active elements understand each other ?

16. 2006 Agent Tag Board Tag boards serve as models for regions of interaction What is the radius of an interactionen ? Regions of local interaction rooms, streets radius of physical effects communication links … Tag A gent Architecture A gent Architecture FTA

17. 2006 Agent Agents can link together several regions of local interaction What is the systems topology ? Tag Board Tag A gent Architecture A gent Architecture FTA

18. 2006 Real topologies can be modeled 1:1 Agent Tag Board Tag A gent Architecture A gent Architecture FTA What is the systems topology ?

19. 2006 3D voxel model for environment landscape model M odelling M odelling Environment

20. 2006 obstruction of radio communication electronic countermeasures 3D voxel model for environment landscape model with radio beam at a hill weather, clouds, mist, smoke visibility shapes of units computationally fast scalable in resolution appropriate for multi-scale features … … M odelling M odelling Environment + Communication

21. 2006 M odes of use M odes of use Nondeterministic Wargaming ITSim Maneuver Control Red PersonsCGF Blue PersonsCGF + Data Farming ITSim Planner Szenario Data Base Maneuver mode Szenario Data Base Data Minig Get empirical knowledge about the szenario Planner / Strategy- Builder Variety of possible traces for different outcomes Variety of possible traces for different outcomes Evaluated non-deterministic szenario Evaluated non-deterministic szenario To know what might happen

22. 2006 ITSim Maneuver Control Red PersonsCGF Blue PersonsCGF Data Farming ITSim Planner Data Minig Szenario Data Base Wargaming Szenario Description C 4 I with szenario data base more coherent behavior no improvisation needed ITSim HQ Armed Forces Combat Support M odes of use M odes of use Combat Support

23. 2006 Multi-scale simulation of scenarios environment communication reporting structures order structures effects Analysis of variables communication load risk measured probabilities of failure Scenario analysis alternative scenarios critical paths demands, costs, … time-dependent factors operation orders, bill of materials training maneuvers … … … … 1 2 Online-C2System (decision support) comparison between stored and current mission graph based on similarity measures. offline preparation online mission scenario database 4 3 Data Farming M odes of use M odes of use Combat Support

24. 2006 Scalable in space, and functionality Finishing the LAMPSSys-Core Finishing of the HLA-Impementation Adapter for statistical Analysis and GIS Scalable in space, and functionality Finishing the LAMPSSys-Core Finishing of the HLA-Impementation Adapter for statistical Analysis and GIS OutlookOutlook

25. 2006 In a simulation the time is run in disc cycles A state S in a point in time t is described by the states of all the individual agents A simulation run is fully described by the set of all states S in all time steps In a simulation the time is run in disc cycles A state S in a point in time t is described by the states of all the individual agents A simulation run is fully described by the set of all states S in all time steps Graph-MetricGraph-Metric

26. 2006 Graph-MetricGraph-Metric

27. For all attributes of all agents in all time steps this is an overwhelming amount of information => we pick interesting attributes beforehand: The position (in the 3D space) The loss of own troops The time to accomplish the mission goal The amount of effects to act upon the opponent For all attributes of all agents in all time steps this is an overwhelming amount of information => we pick interesting attributes beforehand: The position (in the 3D space) The loss of own troops The time to accomplish the mission goal The amount of effects to act upon the opponent Graph-MetricGraph-Metric

28. 2006 Graph-MetricGraph-Metric Clusters over time and runs Markov tree with propabilities at the edges

29. 2006 T echnical Realization T echnical Realization Agent Technology The world consists of concurrent interacting agents (also non-human parts of the game are modeled as agents) The real-world behavior is simulated in detail on a computer as an artificial reality Humans and real systems outside the simulator are coupled with this artificial reality by special communication agents The world consists of concurrent interacting agents (also non-human parts of the game are modeled as agents) The real-world behavior is simulated in detail on a computer as an artificial reality Humans and real systems outside the simulator are coupled with this artificial reality by special communication agents

30. 2006 T hank you for your attention !