The Value of Information for Populations in Varying Environments

The notion of information pervades informal descriptions of biological systems, but formal treatments face the problem of defining a quantitative measure of information rooted in a concept of fitness, which is itself an elusive notion. Here, we present a model of population dynamics where this problem is amenable to a mathematical analysis. In the limit where any information about future environmental variations is common to the members of the population, our model is equivalent to known models of financial investment. In this case, the population can be interpreted as a portfolio of financial assets and previous analyses have shown that a key quantity of Shannon's communication theory, the mutual information, sets a fundamental limit on the value of information. We show that this bound can be violated when accounting for features that are irrelevant in finance but inherent to biological systems, such as the stochasticity present at the individual level. This leads us to generalize the measures of uncertainty and information usually encountered in information theory

SPS WANF Dismantling: A Large Scale-Decommissioning Project at CERN

The operation of the SPS (Super Proton Synchrotron) West Area Neutrino Facility (WANF) was halted in 1998. In 2010 a large scale-decommissioning of this facility was conducted. Besides CERN’s commitment to remove non-operational facilities, the additional motivation was the use of the installation (underground tunnels and available infrastructure) for the new HiRadMat facility, which is designed to study the impact of high-intensity pulsed beams on accelerator components and materials. The removal of 800 tons of radioactive equipment and the waste management according to the ALARA (As Low As Reasonably Achievable) principles were two major challenges. This paper describes the solutions implemented and the lessons learnt confirming that the decommissioning phase of a particle accelerator must be carefully studied as from the design stage

On the Evolution of Investment Strategies and the Kelly Rule – A Darwinian Approach

This paper complements theoretical studies on the Kelly rule in evolutionary finance by studying a Darwinian model of selection and reproduction in which the diversity of investment strategies is maintained through genetic programming. We find that investment strategies which optimize long-term performance can emerge in markets populated by unsophisticated investors. Regardless whether the market is complete or incomplete and whether states are i.i.d. or Markov, the Kelly rule is obtained as the asymptotic outcome. With price-dependent rather than just state-dependent investment strategies, the market portfolio plays an important role as a protection against severe losses in volatile markets

A maximal entropy stochastic process for a timed automaton

International audienceSeveral ways of assigning probabilities to runs of timed automata (TA) have been proposed recently. When only the TA is given, a relevant question is to design a probability distribution which represents in the best possible way the runs of the TA. This question does not seem to have been studied yet. We give an answer to it using a maximal entropy approach. We introduce our variant of stochastic model, the stochastic process over runs which permits to simulate random runs of any given length with a linear number of atomic operations. We adapt the notion of Shannon (continuous) entropy to such processes. Our main contribution is an explicit formula defining a process $Y^*$ which maximizes the entropy. This formula is an adaptation of the so-called Shannon-Parry measure to the timed automata setting. The process $Y^*$ has the nice property to be ergodic. As a consequence it has the asymptotic equipartition property and thus the random sampling wrt. $Y^*$ is quasi uniform