1. Robo-Rescue
Manage and control various forces in a stressed and complicated situations
Robo-Rescue

2. The Situation
Robocup Rescue Simulation is a Large Multi-Agent System which its aim is to manage the disaster when an earthquake happens.
Its main purpose is to provide emergency decision support by integration of disaster information, prediction, planning, and human interface.
Robo-Rescue

3. The Simulator
Robo-Rescue

4. Main Target
Create a solid ground with robust implementation for future investigation.
Robo-Rescue

5. Sub targets Make the Robo Rescue simulator run.
Create a clear framework for implementations of the algorithms. (random walk, shortest path, ect)
Implementing the fisher algorithm among competitive algorithms (greedy and simulated annealing)
Collect and analyze the results we achieved so far.
Robo-Rescue

6. Our Solution We apply Fisher Market Clearing to Rescue Applications
Robo-Rescue

7. Fisher Market Clearing (FMC)
Market model:
n buyers .
e amount of money for each buyer.
m divisible goods.
U matrix of buyer preferences for goods.
Viable FMC solution = price vector
Pareto optimal.
Envy free.
Robo-Rescue

8. Problem Transformation
Market Clearing
Task allocation
Our situation
Buyers
Agents
Fire brigades
Goods
Tasks
Missions of extinguishing buildings
Preference
value of a good
to a buyer
Utility
of assigning
an agent to a task
of a fire brigade unit performing a mission
Robo-Rescue

9. Run example
Robo-Rescue

10. Competitive Solutions
Simulated Annealing
Robo-Rescue

11. Competitive Solutions
Greedy Algorithm
Robo-Rescue

12. The Results
Robo-Rescue

13. The Results
Robo-Rescue

14. The Results
Robo-Rescue

15. The Results
Robo-Rescue

16. Future work Optimizing the fisher algorithm Academic publishing
Using the algorithm for real situation
Robo-Rescue

17. Robo-Rescue