Some uncertainty about flipping a biased coin can be resolved from the sequence of coin sides shown already. We report the exact amounts of predictable and unpredictable information in flipping a biased coin. Fractional coin flipping does not reflect any physical process, being defined as a binomial power series of the transition matrix for "integer" flipping. Due to strong coupling between the tossing outcomes at different times, the side repeating probabilities assumed to be independent for "integer" flipping get entangled with one another for fractional flipping. The predictable and unpredictable information components vary smoothly with the fractional order parameter. The destructive interference between two incompatible hypotheses about the flipping outcome culminates in a fair coin, which stays fair also for fractional flipping.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515336 | PMC |
http://dx.doi.org/10.3390/e21080807 | DOI Listing |
PLoS One
January 2025
Department of Psychology, Crean College of Health and Behavioral Sciences, Chapman University, Orange, California, United States of America.
Accumulating evidence indicates that unpredictable signals in early life represent a unique form of adverse childhood experiences (ACEs) associated with disrupted neurodevelopmental trajectories in children and adolescents. The Questionnaire of Unpredictability in Childhood (QUIC) was developed to assess early life unpredictability [1], encompassing social, emotional, and physical unpredictability in a child's environment, and has been validated in three independent cohorts. However, the importance of identifying ACEs in diverse populations, including non-English speaking groups, necessitates translation of the QUIC.
View Article and Find Full Text PDFPLoS One
January 2025
School of Mathematics and Statistics, College of Science, Rochester Institute of Technology, Rochester, New York, United States of America.
This study presents a novel non-autonomous mathematical model to explore the intricate relationship between temperature and desert locust population dynamics, considering the influence of both solitarious and gregarious phases across all life stages. The model incorporates temperature-dependent parameters for key biological processes, including egg development, hopper growth, adult maturation, and reproduction. Theoretical analysis reveals the model's capacity for complex dynamical behaviors, such as multiple stable states and backward bifurcations, suggesting the potential for sudden and unpredictable population shifts.
View Article and Find Full Text PDFJ Vis
January 2025
Vision and Control of Action (VISCA) Group, Department of Cognition, Development and Psychology of Education, Institut de Neurociències, Universitat de Barcelona, Barcelona, Catalonia, Spain.
The characterization of how precisely we perceive visual speed has traditionally relied on psychophysical judgments in discrimination tasks. Such tasks are often considered laborious and susceptible to biases, particularly without the involvement of highly trained participants. Additionally, thresholds for motion-in-depth perception are frequently reported as higher compared to lateral motion, a discrepancy that contrasts with everyday visuomotor tasks.
View Article and Find Full Text PDFEur J Neurosci
January 2025
Department of Psychology, University of Lübeck, Lübeck, Germany.
Distraction is ubiquitous in human environments. Distracting input is often predictable, but we do not understand when or how humans can exploit this predictability. Here, we ask whether predictable distractors are able to reduce uncertainty in updating the internal predictive model.
View Article and Find Full Text PDFBiomimetics (Basel)
January 2025
Graduate School of Information, Production and Systems, Waseda University, 2-7 Hibikino, Wakamatsu-ku, Kitakyushu 808-0135, Japan.
In recent years, humanoid robot technology has been developing rapidly due to the need for robots to collaborate with humans or replace them in various tasks, requiring them to operate in complex human environments and placing high demands on their mobility. Developing humanoid robots with human-like walking and hopping abilities has become a key research focus, as these capabilities enable robots to move and perform tasks more efficiently in diverse and unpredictable environments, with significant applications in daily life, industrial operations, and disaster rescue. Currently, methods based on hybrid zero dynamics and reinforcement learning have been employed to enhance the walking and hopping capabilities of humanoid robots; however, model predictive control (MPC) presents two significant advantages: it can adapt to more complex task requirements and environmental conditions, and it allows for various walking and hopping patterns without extensive training and redesign.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!