Recently Díaz, Hössjer and Marks (DHM) presented a Bayesian framework to measure cosmological tuning (either fine or coarse) that uses maximum entropy (maxent) distributions on unbounded sample spaces as priors for the parameters of the physical models (https://doi.org/10.1088/1475-7516/2021/07/020). The DHM framework stands in contrast to previous attempts to measure tuning that rely on a uniform prior assumption. However, since the parameters of the models often take values in spaces of infinite size, the uniformity assumption is unwarranted. This is known as (...) the normalization problem. In this paper we explain why and how the DHM framework not only evades the normalization problem but also circumvents other objections to the tuning measurement like the so called weak anthropic principle, the selection of a single maxent distribution and, importantly, the lack of invariance of maxent distributions with respect to data transformations. We also propose to treat fine-tuning as an emergence problem to avoid infinite loops in the prior distribution of hyperparameters (common to all Bayesian analysis), and explain that previous attempts to measure tuning using uniform priors are particular cases of the DHM framework. Finally, we prove a theorem, explaining when tuning is fine or coarse for different families of distributions. The theorem is summarized in a table for ease of reference, and the tuning of three physical parameters is analyzed using the conclusions of the theorem. (shrink)

To thousands of young people, Marx is the prophet, Mao the sword, and Marcuse the ideological spokesman of the Radical New Left. In The Meaning of Marcuse, Dr. Robert W. Marks, Professor of Philosophy at the New School for Social Research, provides a detailed analysis of Marcuse's most important books--Reason and revolution, Eros and civilization, One-dimensional man, An essay on liberation--and offers the first comprehensive overview of this major 20th century thinker.

This chapter discusses the issue of choosing the best computer model for simulating a real-world phenomenon through the process of validating the model’s output against the historical, real-worldData data. Four families of techniques are discussed that are used in the context of validation. One is based on the comparisonComparison of statistical summaries of the historical dataData and the model output. The second is used where the models and dataData are stochastic, and distributions of variables must be compared, and a metricMetric (...) is used to measure their closeness. After exploring the desirable properties of such a measure, the paper compares the third and fourth methods of measuring closeness ofPattern patterns, using an example from strategic market competition. The techniques can, however, be used for validating computer models in any domain. (shrink)

Is your mind the same thing as your brain, or are there aspects of mind beyond the brain's biology? This is the mind-body problem, and it has captivated curious minds since the dawn of human contemplation. Today many insist that the mind is completely reducible to the brain. But is that claim justified? In this stimulating anthology, twenty-five philosophers and scientists offer fresh insights into the mind-brain debate, drawing on psychology, neurology, philosophy, computer science, and neurosurgery. Their provocative conclusion? The (...) mind is indeed more than the brain. (shrink)