The paper describes the scientiic goals of the virtual soccer team \AT Humboldt 98", which was vice champion in RoboCup 98 in Paris. It is the successor of the world champion \AT Humboldt" from RoboCup 97 in Nagoya. The adaptation of \AT Humboldt" to the new rules of the soccer server has started as \AT Humboldt 97" in Paris.

One of the most important tasks in the RoboCup soccer leagues is to build up soccer domain knowledge for decision-making. Therefore, most RoboCup teams adapt tactics graphs to develop their agents’ behavior manually. This is a very laborious and time-consuming

As RoboCup continues its march towards the day when robots play soccer against people, the focus of researchers’ efforts is slowly shifting from low-level systems (vision, motion, self-localization, etc) to high-level systems such as strategy and cooperation. In the Four-Legged League (recently renamed to the Standard Platform League), teams are still struggling with this transition. While the ...

. This paper introduces both the Eco–Be robotic platform and the RoboCup Mixed Reality Competition and the research under development on the FC Portugal team in the context of this league. The Eco-Bes and the Mixed reality competition present an immediate, simple application for developing complete teams for cooperative robotic applications. The Eco-Be is a very small mobile vehicle, also known...

This thesis describes the incremental development and main features of a synthetic multi-agent system called UvA Trilearn 2001. UvA Trilearn 2001 is a robotic soccer simulation team that consists of eleven autonomous software agents. It operates in a physical soccer simulation system called soccer server which enables teams of autonomous software agents to play a game of soccer against each oth...

The RoboCup research initiative has established synthetic and robotic soccer as testbeds for pursuing research challenges in Arti cial Intelligence and robotics This extended abstract focuses on teamwork and learning two of the multi agent research challenges highlighted in RoboCup To address the challenge of teamwork we discuss the use of a domain independent explicit model of team work and an...

The RoboCup is an initiative to promote the development of robotics in a social relevant way. The competition consists of several leagues and it would be beneficial if developments in one league could be reused in other leagues. This paper describes the development of a simulation model for a humanoid robot inside USARSim, which could be the basis of synergy between the Rescue Simulation, Socce...

SPQR + ISocRob is a joint team between two research groups: SPQR (Italy) and IsocRob (Portugal). SPQR (Soccer Player Quadruped Robots) is the group of the Faculty of Engineering at University of Rome “La Sapienza” in Italy, that is involved in RoboCup competitions since 1998 in different leagues (Middle-size 1998-2002, Four-legged since 2000, Real-rescue-robots since 2003, Virtual-rescue and @H...

In this paper we explain how we applied genetic programming to behavior-based team coordination in the RoboCup Soccer Server domain. Genetic programming is a promising new method for automatically generating functions and algorithms through natural selection. In contrast to other learning methods, genetic programming’s automatic programming makes it a natural approach for developing algorithmic...

Opponent modeling in games deals with analyzing opponents’ behavior and devising a winning strategy. In this paper we present an approach to model low level behavior of individual agents using Robocup Soccer Simulation 3D environment. In 2D League, the primitive actions of agents such as Kick, Turn and Dash are known and high level behaviors are derived using these low level behaviors. In 3D Le...