Applying the repeated game framework to multiparty networked applications

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 145-154).This thesis presents repeated game analysis as an important and practical tool for networked application and protocol designers. Incentives are a potential concern for a large number of networked applications. Well-studied examples include routing and peer-to-peer networks. To the extent that incentives significantly impact the outcome of a system, system designers require tools and frameworks to better understand how their design decisions impact these incentive concerns. Repetition is a prevalent and critical aspect of many networking applications and protocols. Most networked protocols and architectures seek to optimize performance over a longer timescale and many have explicit support for repetition. Similarly, most players in networked applications are interested in longer horizons, whether they be firms building a business or typical individuals trying to use a system. Fortunately, the study of repeated interaction between multiple self-interested parties, repeated games, is a well-understood and developed area of economic and game theoretic research. A key conclusion from that literature is that the outcome of the repeated game can differ qualitatively from that of the one-shot game. Nonetheless, the tools of repeated games have rarely if ever been brought to bear on networking problems. Our work presents the descriptive and prescriptive power of repeated game analysis by making specific contributions to several relevant networking problems.(cont.) The applications considered are inherently repeated in practice, yet our research is the first to consider the repeated model for each particular problem. In the case of interdomain routing, we first show that user-directed routing (e.g., overlays) transforms routing into a meaningfully repeated game. This motivates us to consider protocols that integrate incentives into routing systems. In designing such a routing protocol, we again use repeated games to identify important properties including the protocol period and the format of certain protocol fields. Leveraging this insight, we show how it is possible to address the problem of the repeated dynamic and arrive at a more desirable outcome. In the case of multicast overlay networks, we show how repeated games can be used to explain the paradox of cooperative user behavior. In contrast to prior models, our repeated model explains the scaling properties of these networks in an endogenous fashion. This enables meaningful examination of the impact architecture and protocol design decisions have on the system outcome. We therefore use this model, with simulation, to descry system parameters and properties important in building robust networks. These examples demonstrate the important and practical insights that repeated game analysis can yield. Further, we argue that the results obtained in the particular problems stem from properties fundamental to networked applications - and their natural relationship with properties of repeated games.(cont.) This strongly suggests that the tools and techniques of this research can be applied more generally. Indeed, we hope that these results represent the beginning of an increased use of repeated games for the study and design of networked applications.by Michael Moïse Afergan.Ph.D

Beyond Detection: Investing in Practical and Theoretical Applications of Emotion + Visualization

Emotion is a dynamic variable that modulates how we perceive, reason about, and interact with our environment. Recent studies have established that emotion’s influence carries to data analysis and visualization, impacting performance in ways both positive and negative. While we are still in the infancy of understanding the role emotion plays in analytical contexts, advances in physiological sensing and emotion research have raised the possibility of creating emotion-aware systems. In this position paper, we argue that it is critical to consider the potential advances that can be made even in the face of imperfect sensing, while we continue to address the practical challenges of monitoring emotion in the wild. To underscore the importance of this line of inquiry, we highlight several key challenges related to detection, adaptation, and impact of emotional states for users of data visualization systems, and motivate promising avenues for future research in these areas

Learn Piano with BACh: An Adaptive Learning Interface that Adjusts Task Difficulty based on Brain State

We present Brain Automated Chorales (BACh), an adaptive brain-computer system that dynamically increases the levels of difficulty in a musical learning task based on pianists\u27 cognitive workload measured by functional near-infrared spectroscopy. As users\u27 cognitive workload fell below a certain threshold, suggesting that they had mastered the material and could handle more cognitive information, BACh automatically increased the difficulty of the learning task. We found that learners played with significantly increased accuracy and speed in the brain-based adaptive task compared to our control condition. Participant feedback indicated that they felt they learned better with BACh and they liked the timings of the level changes. The underlying premise of BACh can be applied to learning situations where a task can be broken down into increasing levels of difficulty

MYND: Unsupervised Evaluation of Novel BCI Control Strategies on Consumer Hardware

Neurophysiological studies are typically conducted in laboratories with limited ecological validity, scalability, and generalizability of findings. This is a significant challenge for the development of brain-computer interfaces (BCIs), which ultimately need to function in unsupervised settings on consumer-grade hardware. We introduce MYND: A framework that couples consumer-grade recording hardware with an easy-to-use application for the unsupervised evaluation of BCI control strategies. Subjects are guided through experiment selection, hardware fitting, recording, and data upload in order to self-administer multi-day studies that include neurophysiological recordings and questionnaires. As a use case, we evaluate two BCI control strategies ("Positive memories" and "Music imagery") in a realistic scenario by combining MYND with a four-channel electroencephalogram (EEG). Thirty subjects recorded 70.4 hours of EEG data with the system at home. The median headset fitting time was 25.9 seconds, and a median signal quality of 90.2% was retained during recordings.Neural activity in both control strategies could be decoded with an average offline accuracy of 68.5% and 64.0% across all days. The repeated unsupervised execution of the same strategy affected performance, which could be tackled by implementing feedback to let subjects switch between strategies or devise new strategies with the platform.Comment: 9 pages, 5 figures. Submitted to PNAS. Minor revisio

In Vivo Methods to Study Uptake of Nanoparticles into the Brain

Several in vivo techniques have been developed to study and measure the uptake of CNS compounds into the brain. With these techniques, various parameters can be determined after drug administration, including the blood-to-brain influx constant (Kin), the permeability-surface area (PS) product, and the brain uptake index (BUI). These techniques have been mostly used for drugs that are expected to enter the brain via transmembrane diffusion or by carrier-mediated transcytosis. Drugs that have limitations in entering the brain via such pathways have been encapsulated in nanoparticles (based on lipids or synthetic polymers) to enhance brain uptake. Nanoparticles are different from CNS compounds in size, composition and uptake mechanisms. This has led to different methods and approaches to study brain uptake in vivo. Here we discuss the techniques generally used to measure nanoparticle uptake in addition to the techniques used for CNS compounds. Techniques include visualization methods, behavioral tests, and quantitative methods

Networked Applications

This thesis presents repeated game analysis as an important and practical tool for networked application and protocol designers. Incentives are a potential concern for a large number of networked applications. Well-studied examples include routing and peer-to-peer networks. To the extent that incentives significantly impact the outcome of a system, system designers require tools and frameworks to better understand how their design decisions impact these incentive concerns. Repetition is a prevalent and critical aspect of many networking applications and protocols. Most networked protocols and architectures seek to optimize performance over a longer timescale and many have explicit support for repetition. Similarly, most players in networked applications are interested in longer horizons, whether they be firms building a business or typical individuals trying to use a system. Fortunately, the study of repeated interaction between multiple self-interested parties, repeated games, is a well-understood and developed area of economic and game theoretic research.

The State of the Email Address

Electronic mail is an unquestionably vital component of the Internet infrastructure. While the general perception of email is that it “just works, ” surprisingly little data is available to substantiate this claim. While SMTP is a mature technology of over twenty years, the architecture is increasingly strained by both normal and unsolicited load. In this paper we seek to provide a greater understanding of the behavior of Internet email as a system using active measurement. In order to survey a significant, diverse, and representative set of Internet SMTP servers, to which we have no administrative access, we develop a testing methodology that provides an email “traceroute ” mechanism. Using this mechanism, we measure email loss, latency, and errors over the course of a month to popular, random, and Fortune 500 domains. Our initial results are quite unexpected and include non-trivial loss rates, latencies longer than days, and significant and surprising errors. While we present plausible explanations for some of these phenomena, there are several that we cannot, as of yet, explain. By better understanding Internet protocols which lack explicit end-to-end connection semantics, our eventual hope is to derive guidelines for designing future networks and more reliable email systems. 1

Speed-accuracy comparison of navigational interfaces

The goal of this research is to test the effect of different computer interfaces on the amount of time it takes a user to move a cursor from a start point to a target, using Fitts’ Law, a model that describes the performance of pointing of input devices. Participants in a study used a mouse, Xbox 360 controller, and Nintendo Wii remote to point at and select target regions. The goal is to see the effects of interface, distance to the target, and target width on movement time, information throughput, and hit rate. Additional path metrics and the speed-accuracy tradeoff will be covered