Evolutionary design process |
In particular, the following aspects need to be considered:
Simulation setup:
- Accuracy/granularity of the simulation?
- Physical capabilities of the agent + environment
- How many agents, homogeneous/heterogeneous configuration?
- How should the agent interact with the environment/other agents
- Number/type of sensors
- Ability to change the environment (enable stygmergy)
- Must be evolvable
- Smooth search space, not too large
- Genotype-to-phenotype mapping
- There exists literally a zoo on metaheuristic optimization algorihtms (Cuckoo search, Honeybee, Frog leap, Firefly, ...)
- Ability to find global optimum
- Number of tweaking parameters?
- Should contribute to a smooth search space
- Avoid modeling the solution instead of the problem
- Mapping of multiple objectives (or weighted sum?)
- Is a way to implement an evolutionary design task for multi-agent system
- Needs a simulation of the problem
- Interface for sensor/actuator connections to the agents
- Feedback from a simulation run -> objective function
- Written in Java, runs on multiple platforms including Linux, Mac OS, Windows
- FREVO is available as open soure at http://frevo.sourceforge.net/
- FREVO introduction video including installation, setting up a simulation and running it (length 6 minutes)
Literature
- I. Fehérvári and W. Elmenreich. Evolution as a tool to design self-organizing systems. In Proceedings of the 7th International Workshop on Self-Organizing Systems. Springer Verlag, May 2013.
- A. Sobe, I. Fehérvári, and W. Elmenreich. FREVO: A tool for evolving and evaluating self-organizing systems. In Proceedings of the 1st International Workshop on Evaluation for Self-Adaptive and Self-Organizing Systems, Lyon, France, September 2012.
Ok, I'll take a look at it. I was doing a lot of electronics design but now I'm interested in doing some code again.
ReplyDeleteIf you are interested in evolution and optimization you should look up the paper on 'Continuous Gray Code Optimization'. It is a very simple but effective way to do numerical optimizations. In fact the way it works has nothing to do with Gray Codes at all. That is just the route through with the authors discovered it. I have improved versions of it and some additional insights if you should ever be interested.
Sean O'Connor (evospice symbol yahoo symbol com)