RoboCup is an initiative designed to promote the full integration of AI and robotics research.

The CMUNITED-99 simulator team became the 1999 RoboCup simulator league champion by winning all 8 of its games, outscoring opponents by a combined score of 110-0. CMUNITED-99 builds on the successful CMUNITED-98 implementation but also improves on it in many ways. This article gives an overview of CMUNITED-99's improvements over CMUNITED-98.

RoboCup is an initiative designed to promote the full integration of AI and robotics research. Following the success of the first RoboCup in 1997 at Nagoya (Kitano 1998; Noda et al. 1998) and the second RoboCup in Paris in 1998, the Third Robot World Cup Soccer Games and Conferences, RoboCup-99, were held in Stockholm from 27 July to 4 August 1999 in conjunction with the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI-99). There were four different leagues: (1) the simulation league, (2) the small-size real robot league, (3) the middle-size real robot league, and (4) the Sony legged robot league. RoboCup-2000, the Fourth Robot World Cup Soccer Games and Conferences, will take place in Melbourne, Australia, in August 2000.

The CMUNITED-98 simulator team became the 1998 RoboCup simulator league champion by winning all 8 of its games, outscoring opponents by a total of 66-0. CMUNITED-98 builds on the successful cmunited-97 implementation but also improves on it in many ways. This article gives an overview of the cmunited-98 agent skill and multiagent coordination strategies, emphasizing the recent improvements.

The CMUNITED small-robot team became the 1998 RoboCup small-robot league champion, repeating its 1997 victory. This article gives an overview of the cmunited-98 team, focusing on this year's improvements.

By perceiving the with no adverse effects on the achievement world, each fully distributed agent builds a of G. Then, based can be thought of as times at which the on a complex set of behaviors, it chooses an team is "offline." In general (that is, when the agents are Although acting autonomously, each agent "online"), the domain is dynamic and real time, contributes to the overall team's goal. Agents receive sensory p at time t. The world state is directly accessible In the extreme, if q 0 or if x 0, then the to both internal and external behaviors.

Although our previous and processes the images, giving the positions team had accurate navigation, it was not easily of each robot and the ball. This information is interruptible, which is necessary for operating sent to an off-board controller and distributed in a highly dynamic environment. The final design includes a battery of inherent mechanical inaccuracies and module supplying three independent unforeseen interventions from other agents. It also includes a single board RoboCup competition in Paris (Stone, Veloso, containing all the required electronic circuitry and Riley 1999; Kitano et al. 1997). These improvements by an array of four infrared sensors, which include a robust low-level control algorithm, which handles a moving target with is enabled or disabled by the software control.

Robotic soccer is a challenging research domain that involves multiple agents that need to collaborate in an adversarial environment to achieve specific objectives. In this article, we describe CMUNITED, the team of small robotic agents that we developed to enter the RoboCup-97 competition. We designed and built the robotic agents, devised the appropriate vision algorithm, and developed and implemented algorithms for strategic collaboration between the robots in an uncertain and dynamic environment. The article then focuses on the agent behaviors, ranging from low-level individual behaviors to coordinated, strategic team behaviors.

Robotic soccer is a challenging research domain that involves multiple agents that need to collaborate in an adversarial environment to achieve specific objectives. In this article, we describe CMUNITED, the team of small robotic agents that we developed to enter the RoboCup-97 competition. We designed and built the robotic agents, devised the appropriate vision algorithm, and developed and implemented algorithms for strategic collaboration between the robots in an uncertain and dynamic environment. The robots can organize themselves in formations, hold specific roles, and pursue their goals. In game situations, they have demonstrated their collaborative behaviors on multiple occasions. We present an overview of the vision-processing algorithm that successfully tracks multiple moving objects and predicts trajectories. The article then focuses on the agent behaviors, ranging from low-level individual behaviors to coordinated, strategic team behaviors. CMUNITED won the RoboCup-97 small-robot competition at the Fifteenth International Joint Conference on Artificial Intelligence in Nagoya, Japan.

Our research works towards this broad goal from a Machine Learning perspective. We are particularly interested in investigating how an intelligent agent can choose an action in an adversarial environment. We assume that the agent has a specific goal to achieve. We conduct this investigation in a framework where teams of agents compete in a game of robotic soccer. The real system of model cars remotely controlled from off-board computers is under development.