Rage Against the Machines: How Subjects Learn to Play Against Computers

We use an experiment to explore how subjects learn to play against computers which are programmed to follow one of a number of standard learning algorithms. The learning theories are (unbeknown to subjects) a best response process, fictitious play, imitation, reinforcement learning, and a trial & error process. We test whether subjects try to influence those algorithms to their advantage in a forward-looking way (strategic teaching). We find that strategic teaching occurs frequently and that all learning algorithms are subject to exploitation with the notable exception of imitation. The experiment was conducted, both, on the internet and in the usual laboratory setting. We find some systematic differences, which however can be traced to the different incentives structures rather than the experimental environment.learning; fictitious play; imitation; reinforcement; trial & error; strategic teaching; Cournot duopoly; experiments; internet.

Mosquito Phonotaxis Assay

Phonotaxis experiments can provide information on the spectrum of sounds relevant to mosquito acoustic behaviors. It is widely known that males of disease-transmitting species are attracted to tones with frequencies resembling the wingbeat frequencies of their conspecific females. Thus, phonotaxis experiments can be coupled with wingbeat frequency measurements to inform the development of vector control tools such as acoustic traps and lures. This protocol describes how to set up and execute a phonotaxis experimen

Sensory Transduction: Confusing the Senses

SummaryTwo new studies in the fruit fly Drosophila demonstrate unexpected molecular, and mechanistic, overlaps between the different senses. In the centre stand two long-established families of sensory proteins — rhodopsins and TRP channels

Electrophysiological Measurements of Compound Action Potential Responses from the Antennal Nerve in Response to Stimulation

Electrophysiological recordings taken from the antennal nerve can provide essential information on the general auditory condition of the mosquito tested. Furthermore, electrophysiological recordings provide detailed information on what types of stimulation induce the largest nerve responses. When these are used in conjunction with a vibrometer to measure the corresponding movement of the antennal ear during stimulation, a comprehensive overview of hearing function can be obtained. This protocol can be applied to male and female adults from any mosquito strain and can be scaled relative to available resources

Immunohistochemical Staining of the Mosquito Ear

Immunohistochemistry has played a major role in improving our understanding of the anatomy and function of the nervous system. The use of fluorescent dyes that label different antigens reveals how biological tissues are built and how interactions between cells take place. Obtaining this information is particularly important in the case of the mosquito ear given its highly complex anatomy. This protocol describes an immunohistochemical technique to stain the mosquito ear. The first steps of the procedure include the embedding of the tissue in albumin-gelatin and its sectioning into thin slices to allow antibody penetration. The immunohistochemical procedure can be exploited to detect protein expression and localization by using antibodies specifically raised against the protein of interest or that recognize epitope tags fused to proteins using genome editing methods

A Machine Learning-based Framework for Optimizing the Operation of Future Networks

5G and beyond are not only sophisticated and difficult to manage, but must also satisfy a wide range of stringent performance requirements and adapt quickly to changes in traffic and network state. Advances in machine learning and parallel computing underpin new powerful tools that have the potential to tackle these complex challenges. In this article, we develop a general machinelearning- based framework that leverages artificial intelligence to forecast future traffic demands and characterize traffic features. This makes it possible to exploit such traffic insights to improve the performance of critical network control mechanisms, such as load balancing, routing, and scheduling. In contrast to prior works that design problem-specific machine learning algorithms, our generic approach can be applied to different network functions, allowing reuse of existing control mechanisms with minimal modifications. We explain how our framework can orchestrate ML to improve two different network mechanisms. Further, we undertake validation by implementing one of these, mobile backhaul routing, using data collected by a major European operator and demonstrating a 3×reduction of the packet delay compared to traditional approaches.This work is partially supported by the Madrid Regional Government through the TAPIR-CM program (S2018/TCS-4496) and the Juan de la Cierva grant (FJCI-2017-32309). Paul Patras acknowledges the support received from the Cisco University Research Program Fund (2019-197006)

Acoustic Physiology in Mosquitoes

The acoustic physiology of mosquitoes is perhaps the most complex within the entire insect class. Past research has uncovered several of its-sometimes stunningly unconventional-principles, but many mysteries remain. Their solution necessitates a concerted transdisciplinary effort to successfully link the neuroanatomical and biophysical properties of mosquito flagellar ears to the behavioral ecology of entire mosquito populations. Neuroanatomically, mosquito ears can rival those of humans in both complexity and sheer size. The approximately 16,000 auditory hair cells within the human organ of Corti, for example, are matched by the approximately 16,000 auditory neurons in the Johnston's organ of a male Anopheles mosquito. Both human and mosquito ears receive very extensive efferent innervation, which modulates their function in ways that are as yet poorly understood. Different populations of neuronal and nonneuronal cell types divide the labor of the mosquito ear amongst themselves. Yet, what exactly this labor is, and how it is achieved, is at best vaguely known. For the majority of mosquitoes, biologically relevant sounds are inextricably linked to their flight tones. Either these flight tones are (directly) the sounds of interest or they contribute (indirectly) to the production of audible sound through a process called nonlinear distortion. Finally, male ears can generate tones themselves: The generation of an internal "phantom copy" of a female flight tone (or self-sustained oscillation) is believed to aid the male hearing process. Here, we introduce protocols that target the mosquitoes' auditory neuroanatomy, electrophysiology, and behavior to help shed light on some of these issues

Adaptive mechanism for distributed opportunistic scheduling

Distributed opportunistic scheduling (DOS) techniques have been recently proposed for improving the throughput performance of wireless networks. With DOS, each station contends for the channel with a certain access probability. If a contention is successful, the station measures the channel conditions and transmits in case the channel quality is above a certain threshold. Otherwise, the station does not use the transmission opportunity, allowing all stations to recontend. A key challenge with DOS is to design a distributed algorithm that optimally adjusts the access probability and the threshold of each station. To address this challenge, in this paper, we first compute the configuration of these two parameters that jointly optimizes throughput performance in terms of proportional fairness. Then, we propose an adaptive algorithm based on control theory that converges to the desired point of operation. Finally, we conduct a control theoretic analysis of the algorithm to find a setting for its parameters that provides a good tradeoff between stability and speed of convergence. Simulation results validate the design of our mechanism and confirm its advantages over previous works.This work was funded by the European Community's 7th Framework Program FP7/2007-2013 under Grant 317941 (iJOIN) and by the Madrid Regional Government’s TIGRE5-CM program (S2013/ICE-2919)Publicad