Understanding intelligence
RoboCup-98: Robot Soccer World Cup II
RoboCup-98: Robot Soccer World Cup II
Using Hierarchical Dynamical Systems to Control Reactive Behavior
RoboCup-99: Robot Soccer World Cup III
Intelligence Without Reason
Being Reactive by Exchanging Roles: An Empirical Study
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)
Reactivity and Deliberation: A Survey on Multi-Robot Systems
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)
FU-Fighters 2001 (Global Vision)
RoboCup 2001: Robot Soccer World Cup V
Team Cooperation Using Dual Dynamics
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)
Semi-human instinctive artificial intelligence (SHI-AI)
PCAR '06 Proceedings of the 2006 international symposium on Practical cognitive agents and robots
From bio-inspired vs. psycho-inspired to etho-inspired robots
Robotics and Autonomous Systems
Efficient physics-based planning: sampling search via non-deterministic tactics and skills
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Autonomous dynamic reconfiguration in multi-agent systems: improving the quality and efficiency of collaborative problem solving
Harmonic opponent modeling and behavior structure for 3D soccer simulation agent
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
How students teach robots to think: the example of the Vienna cubes a robot soccer team
ACMOS'06 Proceedings of the 8th WSEAS international conference on Automatic control, modeling & simulation
Toni: a soccer playing humanoid robot
RoboCup 2005
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This paper discusses the hierarchical control architecture used to generate the behavior of individual agents and a team of robots for the RoboCup Small Size competition.Our reactive approach is based on control layers organized in a temporal hierarchy. Fast and simple behaviors reside on the bottom of the hierarchy, while an increasing number of slower and more complex behaviors are implemented in the higher levels. In our architecture deliberation is not implemented explicitly, but to an external viewer it seems to be present.Each layer is composed of three modules. First, the sensor module, where the perceptual dynamics aggregates the readings of fast changing sensors in time to form complex, slow changing percepts. Next, the activation module computes the activation dynamics that determines whether or not a behavior is allowed to influence actuators, and finally the actuator module, where the active behaviors influence the actuators to match a target dynamics.We illustrate our approach by describing the bottom-up design of behaviors for the RoboCup domain.