Shrinking cities are often neglected in the context of global urbanization, the tip of the
iceberg that was driven by underlying complex sets of causes. Therefore, it is urgent and …

A general framework is introduced to estimate how much external information has been
infused into a search algorithm, the so-called active information. This is rephrased as a test …

As machine learning models become more widely used in important decision-making
processes, the need for identifying and mitigating potential sources of bias has increased …

Philosophers frequently define knowledge as justified, true belief. We built a mathematical
framework that makes it possible to define learning (increasing number of true beliefs) and …

The fine-tuning of the universe for life, the idea that the constants of nature (or ratios
between them) must belong to very small intervals in order for life to exist, has been debated …

With the rapid growth of large language models, big data, and malicious online attacks, it
has become increasingly important to have tools for anomaly detection that can distinguish …

Fine-tuning studies whether some physical parameters, or relevant ratios between them, are
located within so-called life-permitting intervals of small probability outside of which carbon …

Principal components analysis has been used to reduce the dimensionality of datasets for a
long time. In this paper, we will demonstrate that in mode detection the components of …

Being able to assess and calculate risks can positively impact an agent's chances of
survival. When other intelligent agents alter environments to create traps, the ability to detect …

In this paper, we study learning and knowledge acquisition (LKA) of an agent about a
proposition that is either true or false. We use a Bayesian approach, where the agent …