Difference between revisions of "Application Ideas for Self-organizing Systems"
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(New page: ==Autonomous Transportation Systems== * Pipe systems for transportation of goods ** Autonomous Robots transport goods from A to B ** Goal: ** Agents have to find their way to these pipe sy...) |
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==Autonomous Transportation Systems== | ==Autonomous Transportation Systems== | ||
* Pipe systems for transportation of goods | * Pipe systems for transportation of goods | ||
| − | + | * Autonomous Robots transport goods from A to B | |
| − | + | * Goal: | |
** Agents have to find their way to these pipe systems themselves | ** Agents have to find their way to these pipe systems themselves | ||
** Agents have to move inside the pipe system from A to B | ** Agents have to move inside the pipe system from A to B | ||
Revision as of 14:57, 14 July 2011
Autonomous Transportation Systems
- Pipe systems for transportation of goods
- Autonomous Robots transport goods from A to B
- Goal:
- Agents have to find their way to these pipe systems themselves
- Agents have to move inside the pipe system from A to B
- Problem: if many agents in the system how to organise them to avoid jams, …
Air Traffic Control System
- From top-down system to bottom-up system
- Decentralised
- Constraints, zero-tolerance against error
- Optimise the route
- Agent in the plane knows about other neighbouring planes and applies repulsion
- Identifies the route (on the air)
- Avoid other planes (on the air) – take regulations into account
- Improve quality of service (time departure, ask for priority to leave the airport)
- Reasons
- Many points of failures
- Humans involved – air traffic controller
Self-Organising financial market
- Put software agents into stock markets
- Goal:
- To make market more stable
- Avoid crashes
- To be more in line with economic theory (rational behaviour, faster, act in zero time)
- How (Alternatives)
- All the trading is done by agents
- Trade based on trust
- Build a network of trust, help identify grey-zone
- Population of agents that crawls the market and looks at it in other ways and identifies whether or not product/entity is trustful
- Agents rely on human-like trust (identify healthy from unhealthy products)
- Agents rely in facts on not on emotion or imitation
- Agents identify risks
- Open questions
- How to mix them with human people
- Acceptance?
