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1.
Nat Commun ; 15(1): 1906, 2024 Mar 19.
Article in English | MEDLINE | ID: mdl-38503774

ABSTRACT

Identifying key patterns of tactics implemented by rival teams, and developing effective responses, lies at the heart of modern football. However, doing so algorithmically remains an open research challenge. To address this unmet need, we propose TacticAI, an AI football tactics assistant developed and evaluated in close collaboration with domain experts from Liverpool FC. We focus on analysing corner kicks, as they offer coaches the most direct opportunities for interventions and improvements. TacticAI incorporates both a predictive and a generative component, allowing the coaches to effectively sample and explore alternative player setups for each corner kick routine and to select those with the highest predicted likelihood of success. We validate TacticAI on a number of relevant benchmark tasks: predicting receivers and shot attempts and recommending player position adjustments. The utility of TacticAI is validated by a qualitative study conducted with football domain experts at Liverpool FC. We show that TacticAI's model suggestions are not only indistinguishable from real tactics, but also favoured over existing tactics 90% of the time, and that TacticAI offers an effective corner kick retrieval system. TacticAI achieves these results despite the limited availability of gold-standard data, achieving data efficiency through geometric deep learning.


Subject(s)
Athletic Performance , Athletic Performance/physiology , Qualitative Research , Soccer
2.
Science ; 378(6623): 990-996, 2022 12 02.
Article in English | MEDLINE | ID: mdl-36454847

ABSTRACT

We introduce DeepNash, an autonomous agent that plays the imperfect information game Stratego at a human expert level. Stratego is one of the few iconic board games that artificial intelligence (AI) has not yet mastered. It is a game characterized by a twin challenge: It requires long-term strategic thinking as in chess, but it also requires dealing with imperfect information as in poker. The technique underpinning DeepNash uses a game-theoretic, model-free deep reinforcement learning method, without search, that learns to master Stratego through self-play from scratch. DeepNash beat existing state-of-the-art AI methods in Stratego and achieved a year-to-date (2022) and all-time top-three ranking on the Gravon games platform, competing with human expert players.


Subject(s)
Artificial Intelligence , Reinforcement, Psychology , Video Games , Humans
3.
Prim Care ; 47(3): 529-537, 2020 Sep.
Article in English | MEDLINE | ID: mdl-32718448

ABSTRACT

Human papillomavirus (HPV) is a significant cause of global morbidity and mortality. A nonavalent HPV vaccine is widely available and recommended for routine use at 11 to 12 years old. Older teens and adults though age 45 years also could be offered vaccination. Widespread use of the HPV vaccine appears to impact the rate of infections and cancers. Some parents/teens may hesitate to be vaccinated. The strongest predictor to receiving the vaccine remains a trusted health care professional making a strong recommendation to receive the vaccine. New HPV vaccines are in the pipeline, including therapeutic vaccines to treat HPV-related cancers.


Subject(s)
Neoplasms/prevention & control , Papillomavirus Vaccines/administration & dosage , Primary Health Care/organization & administration , Cultural Characteristics , Drug Development , Female , Global Health , Health Knowledge, Attitudes, Practice , Humans , Neoplasms/epidemiology , Oropharyngeal Neoplasms/epidemiology , Oropharyngeal Neoplasms/prevention & control , Papillomavirus Vaccines/economics , Parents/psychology , Practice Guidelines as Topic , Primary Health Care/standards , Racial Groups , United States , Uterine Cervical Neoplasms/epidemiology , Uterine Cervical Neoplasms/prevention & control , Vaccination Coverage
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