Soccer Server: A Tool for Research on Multiagent Systems

@article{Noda1998SoccerSA,
  title={Soccer Server: A Tool for Research on Multiagent Systems},
  author={I. Noda and H. Matsubara and K. Hiraki and I. Frank},
  journal={Appl. Artif. Intell.},
  year={1998},
  volume={12},
  pages={233-250}
}
This article describes Soccer Server, a simulator of the game of soccer designed as a benchmark for evaluating multiagent systems and cooperative algorithms. In real life, successful soccer teams require many qualities, such as basic ball control skills, the ability to carry out strategies, and teamwork. We believe that simulating such behaviors is a significant challenge for computer science, artificial intelligence, and robotics technologies. It is to promote the development of such… Expand
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References

SHOWING 1-10 OF 31 REFERENCES
Can Situated Robots Play Soccer
TLDR
A soccer tournament has been carried out using the Dynamite testbed to evaluate aspects of the proposed reactive deliberation robot architecture, and the results raise new issues and problems for research on robotic agents operating in dynamic environments. Expand
Real-time intelligent behaviour in dynamic environments : soccer-playing robots
TLDR
The results of the soccer tournament suggest that the architectural elements in reactive deliberation are sufficient for real-time intelligent control in dynamic environments. Expand
RoboCup: The Robot World Cup Initiative
The Robot World Cup Initiative (R, oboCup) is attempt to foster AI and intelligent rohoties research by providing a standard problem where wide range of technologies especially concerning multi-agentExpand
The RoboCup Synthetic Agent Challenge 97
TLDR
This paper presents three specific challenges for the next two years of RoboCup Challenge: learning of individual agents and teams; multi-agent team planning and plan-execution in service of teamwork; and opponent modeling. Expand
Reactive Deliberation: An Architecture for Real-Time Intelligent Control in Dynamic Environments
TLDR
The results suggest that the architectural elements in reactive deliberation are sufficient for real-time intelligent control in dynamic environments. Expand
Behavior coordination for a mobile robot using modular reinforcement learning
  • E. Uchibe, M. Asada, K. Hosoda
  • Engineering, Computer Science
  • Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS '96
  • 1996
TLDR
A method of modular learning which coordinates multiple behaviors taking account of a trade-off between learning time and performance is presented, applied to one to one soccer playing robots. Expand
Non-Physical Intervention in Robot Learning Based on LfE Method
TLDR
An efficient method of robot learning by which a set of pairs of a state and an action are constructed to achieve a goal so that a robot can take an adequate action to achieve the goal from every state. Expand
Towards collaborative and adversarial learning: a case study in robotic soccer
TLDR
This work presents a learned, robust, low-level behavior that is necessitated by the multiagent nature of the domain, viz. shooting a moving ball and discusses the issues that arise as the learning scenario is extended to require collaborative and adversarial learning. Expand
Vision-based reinforcement learning for purposive behavior acquisition
TLDR
A method of vision-based reinforcement learning by which a robot learns to shoot a ball into a goal is presented, and several issues in applying the reinforcement learning method to a real robot with vision sensor are discussed. Expand
The Role of Chess in Artificial Intelligence Research
TLDR
The aim of this paper is to promote chess as the fundamental test bed recognized by its founding researchers and increase awareness of its contribution to date. Expand
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