Dynamics in atomic signaling games

We study an atomic signaling game under stochastic evolutionary dynamics. There is a finite number of players who repeatedly update from a finite number of available languages/signaling strategies. Players imitate the most fit agents with high probability or mutate with low probability. We analyze the long-run distribution of states and show that, for sufficiently small mutation probability, its support is limited to efficient communication systems. We find that this behavior is insensitive to the particular choice of evolutionary dynamic, a property that is due to the game having a potential structure with a potential function corresponding to average fitness. Consequently, the model supports conclusions similar to those found in the literature on language competition. That is, we show that efficient languages eventually predominate the society while reproducing the empirical phenomenon of linguistic drift. The emergence of efficiency in the atomic case can be contrasted with results for non-atomic signaling games that establish the non-negligible possibility of convergence, under replicator dynamics, to states of unbounded efficiency loss

Multiple-Model Adaptive Control With Set-Valued Observers

This paper proposes a multiple-model adaptive control methodology, using set-valued observers (MMAC-SVO) for the identification subsystem, that is able to provide robust stability and performance guarantees for the closed-loop, when the plant, which can be open-loop stable or unstable, has significant parametric uncertainty. We illustrate, with an example, how set-valued observers (SVOs) can be used to select regions of uncertainty for the parameters of the plant. We also discuss some of the most problematic computational shortcomings and numerical issues that arise from the use of this kind of robust estimation methods. The behavior of the proposed control algorithm is demonstrated in simulation.Comment: Combined 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference, 200

Dark Matter from Dark Glueball Dominance

New gauge forces can play an important role in the evolution of the early universe. In this work we investigate the cosmological implications of a pure Yang-Mills dark sector that is dominantly populated after primordial inflation. Such a dark sector takes the form of a bath of dark gluons at high temperatures, but confines at lower temperatures to produce a spectrum of dark glueballs. These glueballs then undergo a freezeout process such that the remnant population is nearly completely dominated by the lightest state. To reproduce the observed cosmology, this lightest glueball species must decay to the Standard Model to repopulate and reheat it. At leading order, this can occur through a connector operator of dimension-6. In contrast, other glueballs can be parametrically long-lived or stable, and remain as contributors to dark matter or modify the observed cosmology through their later decays. In this work we study the evolution of such dark sectors in detail. We demonstrate that stable remnant glueballs can produce the measured dark matter abundance. We also derive broad constraints on non-Abelian dark sectors from overproduction of remnant glueballs when they are stable or from their destructive impact when they are able to decay.Comment: 26 pages, 7 figure

Auditory Short-Term Memory Behaves Like Visual Short-Term Memory

Are the information processing steps that support short-term sensory memory common to all the senses? Systematic, psychophysical comparison requires identical experimental paradigms and comparable stimuli, which can be challenging to obtain across modalities. Participants performed a recognition memory task with auditory and visual stimuli that were comparable in complexity and in their neural representations at early stages of cortical processing. The visual stimuli were static and moving Gaussian-windowed, oriented, sinusoidal gratings (Gabor patches); the auditory stimuli were broadband sounds whose frequency content varied sinusoidally over time (moving ripples). Parallel effects on recognition memory were seen for number of items to be remembered, retention interval, and serial position. Further, regardless of modality, predicting an item's recognizability requires taking account of (1) the probe's similarity to the remembered list items (summed similarity), and (2) the similarity between the items in memory (inter-item homogeneity). A model incorporating both these factors gives a good fit to recognition memory data for auditory as well as visual stimuli. In addition, we present the first demonstration of the orthogonality of summed similarity and inter-item homogeneity effects. These data imply that auditory and visual representations undergo very similar transformations while they are encoded and retrieved from memory