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Law of supply and demand market simulation with intelligent agents on Clonemap

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Vencom

Designed using clonemap, a project of RWTH AACHEN University

Installation

Deploy clonemap's core docker containers:

git clone https://git.rwth-aachen.de/acs/public/cloud/mas/clonemap.git "<folder>"
"<folder>"\deployments\docker docker-compose up -d #REM to start the containers
"<folder>"\deployments\docker docker-compose down

Build Vencom image and deploy docker container/s:

git clone https://github.com/SSII-UEM/Vencom.git "<folder>"
cd "<folder>"
docker build --rm -f build\Dockerfile -t vencom .
curl -X "POST" -d @scenario.json localhost:30009/api/clonemap/mas

Issues

  • Vencom is currently designed to work on a single MAS, so configuring more imagegroups.agents than the config.agentsperagency will not work as expected.

  • Buyers bought products aren't always properly recovered

  • Buyers HP can reach subzero values, agents never die

  • Periodic behaviours introduce racing behaviours while reading/writing (concurrent) each agent properties

  • Coordinate distances aren't properly computed

  • Fronted module is having troubles to show logs

Future additions

  • Products should have a lifespan to incentivate retailers to design better market strategies and buyers to eat them before others they own

  • Buyers should be able to generate an income by themselves in order to survive. That means working, stealing, gifting...

  • Agents are located on a 3D map, so it would be interesting to make them able to move (retailers to find better spots to sell, buyers better spots in order to perform their activities)

  • Retailers should also have the same capabilities as buyers. That means they should also need to consume products to survive.

  • Intelligence

Difficulties

  • Debugging is very difficult

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