A Hybrid Online Off-Policy Reinforcement Learning Agent Framework Supported by Transformers.

Reinforcement learning (RL) is a powerful technique that allows agents to learn optimal decision-making policies through interactions with an environment. However, traditional RL algorithms suffer from several limitations such as the need for large amounts of data and long-term credit assignment, i.e.

Modeling Dynamical Positional Physical Data on Field Zones Occupied by Playing Positions in Elite-Level Futsal: A Comparison Between Running Velocities, Accelerations, and Decelerations.

Serrano, C, Felipe, JL, García-Unanue, J, Vicente Gimenez, J, Jiménez-Linares, L, Ibáñez, E, Hernando, E, Gallardo, L, and Sánchez-Sánchez, J. Modeling dynamical positional physical data on field zones occupied by playing positions in elite-level futsal: a comparison between running velocities, acceleration, and deceleration. J Strength Cond Res 37(1): 200-206, 2023-The aim of this study was to analyze the influence of playing positions on the physical demands and the specific court zones occupied during official futsal games.

Characterisation of Goal Scoring Patterns during Open Play Related to Zone Pitch Division and Number of Players Involved in the 2018 FIFA World Cup.

The aim of this study was to characterise all the goal scoring patterns during open play (elaborate attacks versus counterattacks) related to zone pitch division and the number of players involved in the 2018 FIFA World Cup in Russia. An Iterative Dichotomiser 3 (ID3) decision tree algorithm was used to classify all the goal scoring patterns (94 goals in 64 matches). The results did not show statistical differences between the type of scoring goal during the 2018 FIFA World Cup ( > 0.