Opponent modeling is the ability to use prior knowledge and observations in order to predict
the behavior of an opponent. This survey presents a comprehensive overview of existing …

Effective team strategies and joint decision-making processes are fundamental in modern
robotic applications, where multiple units have to cooperate to achieve a common goal. The …

Abstract The Small Size Robot League (SSL) was among the founding RoboCup leagues in
the 1997 competition held during IJCAI'97 in Nagoya, Japan. Since then, the league has …

Currently, no artificial intelligence (AI) agent can beat a professional real-time strategy game
player. Lack of effective opponent modeling limits an AI agent's ability to adapt to new …

In this paper, we propose a new method for classifying the strategies of an opponent in the
RoboCup Soccer Small-Size League. Each strategy generates a sequence of basic actions …

RoboCup soccer competitions are considered among the most challenging multi-robot
adversarial environments, due to their high dynamism and the partial observability of the …

Having a good estimation of the robot-players positions is becoming imperative to
accomplish high level tasks in any RoboCup League. Classical approaches use a vector …

The paper presents an approach to perform post-hoc analysis of RoboCup Soccer
Simulation 3D teams via log files of their matches and to learn a model to classify them not …

The ability to estimate future events is essential for biological systems to adapt themselves to
uncertain situations efficiently. Similarly, the abilities to estimate tactical movements of …

The efficient coordination of soccer robots is a complex topic because there are numerous
possible scenarios in the game, and the state of the robots can change rapidly. It requires …