Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

SIMULATORS AS DRIVERS OF CUTTING EDGE

RESEARCH

Muhammad Adil Raja

Roaming Researchers, Inc.

cbnd

February 7, 2016

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

OUTLINE I

1 MOTIVATION

2 INTRODUCTION

3 A RATIONALE FOR ADOPTING SIMULATORS

4 SIMULATORS FOR OTHER FEATS

5 HOW GOOD IS THE SIMULATED STUFF?

6 INNOVATION THROUGH SIMULATION

7 POPULAR SIMULATORSSoftware Dovetailing Issues

8 APPLICATION INTEGRATION SOFTWARE

9 INTERACTIONS WITH FLIGHTGEAR

10 CONCLUSIONS

11 REFERENCES

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

MOTIVATION

Problems of research.Bewildered early stage researchers.Lack of appropriate problems.How should we find and solve problems?In order to conduct good quality research in variousscientific and academic disciplines, it is not only important,rather inevitable to employ simulators.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

INTRODUCTION

Why this presentation?Why do people use simulators?

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

SIMULATORS AND ESCAPISM

Traditional motives for using simulators.To avoid responsibility.To avoid programming.Doing a bunch of simulations could save a lot of time andmental effort.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

A RATIONALE FOR ADOPTING SIMULATORS I

Availability of advanced simulation software andframeworks.There are obvious advantages of them.Traditionally, most of the engineering feats have requiredspecialized human experts.An engineer spends years in learning a particular set ofskills.The manufacturing process, whether automated orrequiring manual labour, has had to address all theunderpinnings of the successful development of thetechnology.The recent advances in computing technologies havechanged this.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

A RATIONALE FOR ADOPTING SIMULATORS II

The arrival of cloud computing technologies, coupled withadvancements in computing hardware, have begun toenable the realization of the numerous fantasticengineering gadgets that were possible only theoreticallypreviously.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

AN EXAMPLE FROM SOLAR ENERGY SYSTEMS

The solar energy panels were developed previously bydomain-experts.A certain product specification which addressed theelectrical and physical properties of the panel to bedeveloped.At the very best the engineer had access to a simulationsoftware that could be used to simulate a solar panel ofdesired specifications.Successful designing followed by fabrication.Designing was a black-art.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

A PARADIGM SHIFT

Current advances in computing technologies havechanged such trends.Simulators can be designed and developed that allow thetarget technology to be emulated to best match the targetspecifications.Power of the cloud is a driving force.Augmenting a simulator with a machine learning (ML)algorithm speeds up the design process.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

A REFLECTION ON ML

A sub-field of artificial intelligence.A computing machine is expected to learn to find solutionsto a user-specified problem all by itself with minimal humanintervention.A machine is provided with a specification of the problem,along with relevant data, and it is expected to find asolution for the problem all by itself.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

ADVANTAGES OF ML

1 The overall development life-cycle can be automated.2 As the development life-cycle is mostly automated,

workable prototypes of desired products can be producedwith a lot more agility.

3 Despite producing counter-intuitive models, achievedmodels are often a lot more efficient than what could havebeen achieved by a hand-crafted counterpart.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

LIMITATIONS OF ML

ML algorithms should work with simulators or emulators.As ML algorithms make progress in finding an optimalsolution for the problem at hand, they do so by makingerrors.ML algorithms have to be allowed to make errors as theyproceed to find optimal solutions.By making errors they tend to escape the regions ofsub-optimal solutions and move to more optimal regions ofthe solution space.It becomes prohibitive to employ them to real systems tofind solutions.Computational requirements are also a concern!

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

AN EXAMPLE FROM VEHICLE ROUTING I

An ML algorithm can be used to address a vehicle routingproblem in which the algorithm trains a vehicle tosuccessfully traverse a path by fulfilling certain userspecified objectives.In finding the optimal solution, a typical algorithm willnormally generate a large number of candidate solutionsrandomly and improve them (or their successors)iteratively over time or several generations.Since the initial solutions are chosen randomly, they can beexpected to be erroneous.The vehicle they govern will crash with a high probability.It is only due to the guided nature of the underlying searchalgorithm that solutions begin to improve after a certainnumber of iterations.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

AN EXAMPLE FROM VEHICLE ROUTING II

Eventually a routing pattern begins to emerge that canlead the vehicles to the desired destinations successfully.

Now assume what would happen if such an algorithm wasrun to address the vehicle routing problem using realvehicles.

Clearly, as erroneous solutions are deliberately producedand tested with real vehicles, quite a lot of them would endup in catastrophic crashes.

This can make the whole enterprise of solving vehiclerouting problems unaffordable.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

SIMULATORS FOR OTHER FEATS

The rationale for employing simulators can be consideredto hold for many other feats.Consider the problem of discovering an optimal design fora solar energy panel.Clearly, one approach could be to design a new panel fromscratch by hand.Such a design would naturally be a function of the whimsand caprices of the designer.Another approach could be to employ a suitable MLalgorithm to do the job of design discovery.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

HOW GOOD IS THE SIMULATED STUFF?

It all depends on how good are the simulators.Accurate simulators shall develop accurate systems.A vehicular simulation system should model everything asperfectly as possible to mimic the real world.Moreover, the environment of the vehicle should also bemodelled as perfectly as possible.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

INNOVATION THROUGH SIMULATION I

Unmanned aerial vehicles.

Solar energy systems.

Social and ecosystem modelling.

Vehicle routing.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

POPULAR SIMULATORS I

Flight:FlightGear Craighead et al. (2007).Microsoft flight simulator Williams (2006).X-Plane Bittar et al. (2014)

Ecosystem:Echo, Avida, Polyworld, BubbleWorld.Evo, Farmsticks andEcosim Gras et al. (2015).

Social:Mason Luke et al. (2004).

Power:UWPFLOW, AMES, THYME, TEFTS, DCOPFJ, minpower,MatPower, OpenDSS, Dome, PSAT, MatDyn, 4DIAC,InterPSS, PowerSystems, MatACDC, GridLAB-D,OpenETran, OpenPMU, rapid61850, OpenlEC andliblEC Comittee (2013).

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

POPULAR SIMULATORS II

Wind:RETScreen, wind data generator (WDG) are used forfeasibility analysis.QBlade and Vortexje are open-source simulators for turbinedesign.WindSim, ZephyTOOLS and Windie are for flow modelling.openWind, WindFarmer, WindPRO, meteodyn WT andWindSim are for wind farm modelling.openWind and WindPRO are for farm visualization.HiRLAM and GFS are for prediction Ximo (2012).

Solar:RETScreen, PV F-Chart, SolarDesignTool, INSEL,TRNSYS, NREL Solar Advisor Model, ESP-r 11.5,PVSYST 4.33, SolarPro, PV DesignPro-G, PV*SOL Expertand HOMER Lalwani et al. (2010).

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

SOFTWARE DOVETAILING ISSUES I

How to dovetail domain-specific simulators with variousmachine learning algorithms.It would be ideal to come up with a general applicationintegration framework that accepts a pair of a randomlychosen simulator and an ML algorithm and dovetails them.Integration should be such that the ML algorithm should beable to invoke various objects in the simulator, performcomputations on them and adapt its states according tothe performance of those objects.As various ML algorithms implement some sort of aniterative mechanism, a natural requirement could be tohave a means of data transfer between the pair ofapplications.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

SOFTWARE DOVETAILING ISSUES II

Data transfer can be required to test the solutionsgenerated by the learning algorithm using the simulator.So, a repetitive data transfer back and forth between thetwo applications should be naturally sought.There are other objectives a nice dovetailing applicationshould also address. For instance, it would be quiteworthwhile if the dovetailing application can exploit thecomputing power of a distributed computing environment,such as a cloud.Such issues would have to be taken into account whiledeveloping the dovetailing application, and should beincluded in its software design issues to be addressed.At present such dovetailing applications do not exist thatintegrate a randomly chosen pair of a machine learningalgorithm and a domain-specific simulator.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

APPLICATION INTEGRATION SOFTWARE

Apache Camel.Talend ESB.AnyPoint Studio By MuleSoft.Matlab and Octave.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

INTERACTIONS WITH FLIGHTGEAR

Implemented in C.Wrapped in Nasal.Comes with full-fledged Telnet and http servers.Can be interfaced with Matlab: Matlab interface forFlightGear.Through Matlab it can be integrated with numerous MLalgorithms.A wide variety of aircraft can be modelled.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

CONCLUSIONS

This position paper argues about the viability of employingsimulators for cutting-edge research.Recent advancements in computing systems are openingendless possibilities to simulate real-world phenomena thatwere traditionally only possible in human imagination andthought experiments.With the sophistication that is being achieved by simulationframeworks, it is now more convenient to simulate varioustypes of problems.The real world artefacts can be created afterwards, aftersimulations have succeeded.This is not only supposed to reduce production costs, but ahandful of other benefits are conceived and presented.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

REFERENCES I

Bittar, A., de Oliveira, N. M. F., and de Figueiredo, H. V. (2014).Hardware-in-the-loop simulation with x-plane of attitudecontrol of a suav exploring atmospheric conditions. Journalof Intelligent & Robotic Systems, 73(1-4):271–287.

Comittee, I. P. (2013). Task force on open source software forpower systems. http://ewh.ieee.org/cmte/psace/CAMS_taskforce/software.htm.

Craighead, J., Murphy, R., Burke, J., and Goldiez, B. (2007). Asurvey of commercial & open source unmanned vehiclesimulators. In Robotics and Automation, 2007 IEEEInternational Conference on, pages 852–857. IEEE.

Gras, R., Golestani, A., Hendry, A. P., and Cristescu, M. E.(2015). Speciation without pre-defined fitness functions.PLoS ONE, 10.

Motivation Introduction A Rationale for Adopting Simulators Simulators for Other Feats How Good is the Simulated Stuff? Innovation Through Simulation Popular Simulators Application Integration Software Interactions With FlightGear Conclusions References References

REFERENCES II

Lalwani, M., Kothari, D., and Singh, M. (2010). Investigation ofsolar photovoltaic simulation softwares. International journalof applied engineering research, 1(3):585–601.

Luke, S., Cioffi-Revilla, C., Panait, L., and Sullivan, K. (2004).Mason: A new multi-agent simulation toolkit. In Proceedingsof the 2004 swarmfest workshop, volume 8, page 44.

Williams, B. (2006). Microsoft Flight Simulator as a training aid:a guide for pilots, instructors, and virtual aviators. AviationSupplies & Academics.

Ximo, C. (2012). Wind Energy Software. Ject Press.