Military Reconstructive Simulation in the Cloud to Aid Battlefield Excavations
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Military Reconstructive Simulation in the Cloud to Aid Battlefield Excavations

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Archaeological studies on battlefields may see great benefits from simulated military engagements: simulations help testing hypotheses based on historical data and may also help with validating ...

Archaeological studies on battlefields may see great benefits from simulated military engagements: simulations help testing hypotheses based on historical data and may also help with validating methodologies used on the site. Such methods, however, require high-performance computing expertise and considerable computational power. With the emergence of on-demand computing instances in the cloud, distributed computations have become available to technically every organization or individual. This puts large-scale battlefield simulations within the reach of archaeologists, and the cloud paradigm also lowers the required technological expertise, potentially leading to a more widespread adoption of such simulation methods.

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Military Reconstructive Simulation in the Cloud to Aid Battlefield Excavations Presentation Transcript

  • 1. Military Reconstructive Simulation in the Cloud to Aid Battlefield ExcavationsPeter Wittek – University of BorasXavier Rubio-Campillo – Barcelona Supercomputing Centre 1
  • 2. Introduction Agent-Based Modelling is one of the most promising social simulation techniques. Despite its promises, the use of ABM is still limited in Humanities & Social SciencesCan we improve the methodology using cloud computing?
  • 3. Reconstructing military engagements Why do we need to simulate the past? Agent-Based Modelling of past conflicts Computational challenges A case study: improving battlefield archaeology using distributed ABM Discussion
  • 4. Classical Agent-Based Modelling Inspired on SugarScape model Two key concepts: Agent → individual entity Environment → cellular automata The agent is defined by: Attributes defining its internal state A “step” method containing predefined rules of behavior
  • 5. Some issues Size of simulation: some emergent properties are scale-dependent Number of simulations? Complex analysis of simulations: Spatiotemporal patterns Visualization of multivariate statistics Predefined Behavior
  • 6. Self-fulfilling prophecy Rule-based behavior is interesting for simple models, but... Can we extend them to realistic models? Can we avoid hand-coded self-fulfilling prophecies? Is it possible to validate the scientific quality of complicated models? What about replication?
  • 7. Goal Oriented Agents A possible solution is the introduction of advanced AI agents. Can we create goal-oriented agents? Each time step our agents will: Update knowledge Build a model of their environment Construct a plan of actions to achieve goals
  • 8. Goal Oriented Agents
  • 9. Next step forward...HPC? These solutions show the need to improve computing resources for scientific social simulations: a. More executions b. Larger simulations c. Advanced AI agents a can be easily fixed with several computers executing simulations sequentially b & c will need distributed memory architectures: Clusters Cloud Computing High-Performance Computing
  • 10. The Pandora framework We need specific utilities to execute a simulation in a distributed environment. Pandora is an open-source C++ framework developed to accomplish this task: Automatic generation of code for parallel execution Cassandra: an ABM visualization tool GIS support (GRASS) Statistical support (R package) Key concepts: Agent & World
  • 11. HPC in the cloud Social science projects should be able to develop computing intensive ABMs even if they dont have access to supercomputers The use of a cloud-based Beowulf cluster could solve this problem What if an ABN could be deployed in any Beowulf computer cluster?
  • 12. Deploying Pandora in the cloud
  • 13. A practical case study Computer simulation of a XVIIIth century battlefield archaeological excavation 13
  • 14. Battlefield Archaeology Archaeologists find the result of concentrating thousands of humans and machines in a small space during a small step of time (1-2 days) The methodology dates from 1970, and is based on the use of metal detectors through a systematic exploration of terrain. It has been modernized by the introduction of Geographical Information Systems and GPS: Individual tracking of explored routes and remains Spatial Analysis Geostatistics
  • 15. Methodology
  • 16. Methodology
  • 17. Questions Can we distinguish the dynamics of combats? Can we calculate...? Combat distance Number of soldiers Direction of combat Result (advances, retreats...) In addition, how can archaeological works affect interpretation? Are our hypothesis well based? To answer these questions we developed an Agent-Based Model of the battle AND the excavation
  • 18. Visualization: Cassandra
  • 19. Analysis: R & Grass
  • 20. Discussion Agent-Based Models are well suited to generate virtual archaeological records. The technique requires high computational costs (to model individual behavior and explore parameter space). Cloud Computing can fulfill these needs if researchers have the correct tools to model their problems.
  • 21. Conclusion A decrease in the technological barrier of simulation can be accomplished combining tools like Pandora with Cloud Computing. Once a simulation is deployed, the image can be shared between researchers, and the models reused. Cloud Computing provides to Humanities departments without access to supercomputers a reasonable solution to deal with computational costs.
  • 22. Thank you! ABM can improve the way battlefields are excavated Cloud-based HPC can solve the computational challenge of these simulations The increase in CPU power will benefit the research on Humanities xavier.rubio@bsc.es If you are interested you can test Pandora at: http://github.com/xrubio/pandora 22