Self-Organizing Maps
Situation Based Strategic Positioning for Coordinating a Team of Homogeneous Agents
Balancing Reactivity and Social Deliberation in Multi-Agent Systems, From RoboCup to Real-World Applications (selected papers from the ECAI 2000 Workshop and additional contributions)
COACH UNILANG - A Standard Language for Coaching a (Robo)Soccer Team
RoboCup 2001: Robot Soccer World Cup V
FC Portugal Team Description: RoboCup 2000 Simulation League Champion
RoboCup 2000: Robot Soccer World Cup IV
The focussed D* algorithm for real-time replanning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Hi-index | 0.00 |
This paper presents a hybrid behaviour process for performing collaborative tasks and coordination capabilities in a rescue team. RoboCup Rescue simulator and its associated international competition are used as the testbed for our proposal. Unlike other published work in this field one of our main concerns is having good results on RoboCup Rescue championships by emerging behaviour in agents using a biological paradigm. The benefit comes from the hierarchic and parallel organisation of the mammalian brain. In our behaviour process, Artificial Neural Networks are used in order to make agents capable of learning information from the environment. This allows agents to improve several algorithms like their Path Finding Algorithm to find the shortest path between two points. Also, we aim to filter the most important messages that arise from the environment, to make the right choice on the best path planning among many alternatives, in a short time. A policy action was implemented using Kohonen’s network, Dijkstra’s and D* algorithm. This policy has achieved good results in our tests, getting our team classified for RoboCup Rescue Simulation League 2005.