AIMC Topic: Competitive Behavior
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PursuitNet: A deep learning model for predicting competitive pursuit-like behavior in mice.
Brain research
Apr 8, 2025
Predator-prey interactions exemplify adaptive intelligence refined by evolution, yet replicating these behaviors in artificial systems remains challenging. Here, we introduce PursuitNet, a deep learning framework specifically designed to model the co...
Prediction of talent selection in elite male youth soccer across 7 seasons: A machine-learning approach.
Journal of sports sciences
Dec 17, 2024
This study aimed to investigate the relative importance of parameters from several domains associated to both selecting or de-selecting players with regards to the next age group within a professional German youth soccer academy across a 7-year perio...
Early specialization in formative basketball: A machine learning analysis of shooting patterns in U14 and professional players.
Journal of sports sciences
Dec 12, 2024
Growing evidence supports that early sport specialization in children and adolescents may compromise long-term athlete development and high-performance acquisition. This study aimed to determine the presence of specialised shooting roles in formative...
Identifying Key Training Load and Intensity Indicators in Ice Hockey Using Unsupervised Machine Learning.
Research quarterly for exercise and sport
Jul 3, 2024
To identify key training load (TL) and intensity indicators in ice hockey, practice, and game data were collected using a wearable 200-Hz accelerometer and heart rate (HR) recording throughout a four-week (29 days) competitive period (23 practice ses...
Association between match-related physical activity profiles and playing positions in different tasks: A data driven approach.
Journal of sports sciences
Apr 4, 2024
Assessing the intensity characteristics of specific soccer drills (matches, small-side game, and match-based exercises) could help practitioners to plan training sessions by providing the optimal stimulus for every player. In this paper, we propose a...
Outracing champion Gran Turismo drivers with deep reinforcement learning.
Nature
Feb 9, 2022
Many potential applications of artificial intelligence involve making real-time decisions in physical systems while interacting with humans. Automobile racing represents an extreme example of these conditions; drivers must execute complex tactical ma...
An autonomous debating system.
Nature
Mar 17, 2021
Artificial intelligence (AI) is defined as the ability of machines to perform tasks that are usually associated with intelligent beings. Argument and debate are fundamental capabilities of human intelligence, essential for a wide range of human activ...
The tactics of successful attacks in professional association football: large-scale spatiotemporal analysis of dynamic subgroups using position tracking data.
Journal of sports sciences
Oct 27, 2020
Association football teams can be considered complex dynamical systems of individuals grouped in subgroups (defenders, midfielders and attackers), coordinating their behaviour to achieve a shared goal. As research often focusses on collective behavio...
Multi-AI competing and winning against humans in iterated Rock-Paper-Scissors game.
Scientific reports
Aug 17, 2020
Predicting and modeling human behavior and finding trends within human decision-making processes is a major problem of social science. Rock Paper Scissors (RPS) is the fundamental strategic question in many game theory problems and real-world competi...
Functional magnetic resonance imaging multivoxel pattern analysis reveals neuronal substrates for collaboration and competition with myopic and predictive strategic reasoning.
Human brain mapping
Jul 7, 2020
Competition and collaboration are strategies that can be used to optimize the outcomes of social interactions. Research into the neuronal substrates underlying these aspects of social behavior has been limited due to the difficulty in distinguishing ...
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