Enumerative combinatorics
Artificial Intelligence - Special issue on Robocop: the first step
Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer
Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer
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)
FC Portugal 2001 Team Description: Flexible Teamwork and Configurable Strategy
RoboCup 2001: Robot Soccer World Cup V
Journal of Artificial Intelligence Research
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Managing a team of heterogeneous robots in a dynamic environment poses a challenging job. In this paper a model for a multi-purpose, real-time, adaptable, strategical coordination layer is presented. Based on previous work developed for the RoboCup Soccer simulation, small-size, middle-size and legged leagues, a generic coordination model was built. As both centralized and distributed environment are handled by the layer, communication was an important factor to consider only introducing a minor overhead. A multi-level hierarchical approach was followed with hybrid methods used to switch between concepts. The model was tested with two strategy instances, RoboCup Rescue Simulation and RoboCup Soccer. Strategies are designed with the help of a graphical tool. Results achieved by the team in RoboCup Rescue and Soccer Simulation competitions demonstrate the usefulness of this approach.