Results 101 to 110 of about 1,886 (227)

A Blotto game with incomplete information [PDF]

open access: yes, 2009
We consider a Blotto game with Incomplete Information.
Adamo, Tim, Matros, Alexander
core  

The Role of Gene Flow in the Diversification of the Monkey Treefrog Complex Across the South American Dry Diagonal

open access: yesZoologica Scripta, Volume 55, Issue 4, Page 568-588, July 2026.
ABSTRACT Understanding Neotropical megadiversity remains challenging due to fundamental taxonomic issues, including identifying and describing cryptic species and their distribution, and the limited knowledge of key factors driving biological diversification. Such challenges are especially prominent in diverse clades with high levels of cryptic species,
Felipe Camurugi   +10 more
wiley   +1 more source

A Note on the Core of a Profit-Center Game with Incomplete Information and Increasing Returns to Scale [PDF]

open access: yes
An existence theorem of a full-information revealing core plan of a profit-center game with incomplete information and increasing returns to scale is given.
Sakaki, Yuki
core  

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

open access: yesAdvanced Science, Volume 13, Issue 35, 24 June 2026.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu   +4 more
wiley   +1 more source

Contagion through Learning [PDF]

open access: yes
We study learning in a large class of complete information normal form games. Players continually face new strategic situations and must form beliefs by extrapolation from similar past situations.
Jakub Steiner, Colin Stewart
core  

A Fully Bayesian Approach to Adult Skeletal Age Estimation: Multivariate Latent Trait Modeling With Markov Chain Monte Carlo Sampling

open access: yesAmerican Journal of Biological Anthropology, Volume 190, Issue 2, June 2026.
Ordered probit regression is used as a latent trait model, with age at death estimated from a Gompertz distribution. Combined with Bayesian Markov Chain Monte Carlo sampling, this approach eliminates the need for reference priors for transition ages or population parameters.
Nils Müller‐Scheeßel   +2 more
wiley   +1 more source

HIERARCHIES OF BELIEF AND INTERIM RATIONALIZABILITY [PDF]

open access: yes
In games with incomplete information, conventional hierarchies of belief are incomplete as descriptions of the players’ information for the purposes of determining a player’s behavior.
MARCIN PESKI, JEFFREY C. ELY
core  

Bridging research, policy, and practice: Advancing evidence‐informed approaches for dementia care and prevention: An expert review by the Health Policy Professional Interest Area from ISTAART

open access: yesAlzheimer's &Dementia: Behavior &Socioeconomics of Aging, Volume 2, Issue 2, June 2026.
Abstract Bridging dementia research and policy remains a global challenge, with gaps in governance, capacity, data infrastructure, and contextual fit limiting the development and implementation of effective national dementia plans. To inform this issue, the Health Policy Professional Interest Area of the International Society to Advance Alzheimer's ...
Juliana Souza‐Talarico   +17 more
wiley   +1 more source

Rationalizability and Minimal Complexity in Dynamic Games

open access: yes
This paper presents a formal epistemic framework for dynamic games in which players, during the course of the game, may revise their beliefs about the opponents'' utility functions.
Perea,Andrés
core  

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

open access: yesDeep Underground Science and Engineering, Volume 5, Issue 2, Page 446-464, June 2026.
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan   +4 more
wiley   +1 more source

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