Abstract
RoboCupRescue Simulation System is a platform for designing and implementing various artificial intelligent issues, and it is a very good test bed for solving Multiagent problems. One of the most important aspects of agent design in AI is the way agent acts or responds to the environment that the agent acting upon. An effective action selection and behavioral method requires a good priority extraction method for finding the best actions. In rescue simulation environments, Firebrigades should select fire points in a collaborative manner such that the total achieved result is optimized. In this work we are going to compare two different methods of fire selection in Firebrigade agents in RoboCupRescue Simulation. The first one is priority extraction using delayed rewards and the other one is Fuzzy Neural Network Based Fire Planning.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
