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Bargaining and Pricing in Networked Economic Systems
, 2011
"... Economic systems can often be modeled as games involving several agents or players who act according to their own individual interests. Our goal is to understand how various features of an economic system affect its outcomes, and what may be the best strategy for an individual agent. In this work, w ..."
Abstract

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Economic systems can often be modeled as games involving several agents or players who act according to their own individual interests. Our goal is to understand how various features of an economic system affect its outcomes, and what may be the best strategy for an individual agent. In this work, we model an economic system as a combination of many bilateral economic opportunities, such as that between a buyer and a seller. The transactions are complicated by the existence of many economic opportunities, and the influence they have on each other. For example, there may be several prospective sellers and buyers for the same item, with possibly differing costs and values. Such a system may be modeled by a network, where the nodes represent players and the edges represent opportunities. We study the effect of network structure on the outcome of bargaining among players, through theoretical
Research Statement
"... Summary I am interested in (1) the design of intelligent agents and systems, primarily guided by machine learning; (2) modeling and understanding collective dynamics that result from intelligent individual behavior; and (3) using this understanding to inform the design of venues where people and aut ..."
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Summary I am interested in (1) the design of intelligent agents and systems, primarily guided by machine learning; (2) modeling and understanding collective dynamics that result from intelligent individual behavior; and (3) using this understanding to inform the design of venues where people and automated agents come together to interact. A central focus of my research is on understanding how information flows through systems, how it can be best used by intelligent agents, and how its presence, absence, or the form in which it is available impacts decisions at the individual and systemic levels. My work can be categorized into four broad themes. 1: Collective intelligence I am interested in both modeling and understanding the dynamics of collective intelligence, and in designing algorithms that allow us to use the power of collective wisdom to make better decisions. I have been working on the foundations of a rigorous theory of how information grows in novel social media like Wikipedia and the blogosphere, and on information aggregation and dissemination in prediction markets. In recent work, we have documented some remarkable regularities in the life cycles of average Wikipedia pages and blog posts [26, 27]. They exhibit a concave rise to an editing / commenting peak, followed by decay at a 1/t rate over time. We have proposed a simple model of information creation that matches the data
Bandit Market Makers
"... We propose a flexible framework for profitseeking market making by combining cost function based automated market makers with bandit learning algorithms. The key idea is to consider each parametrisation of the cost function as a bandit arm, and the minimum expected profits from trades executed duri ..."
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We propose a flexible framework for profitseeking market making by combining cost function based automated market makers with bandit learning algorithms. The key idea is to consider each parametrisation of the cost function as a bandit arm, and the minimum expected profits from trades executed during a period as the rewards. This allows for the creation of market makers that can adjust liquidity and bidasks spreads dynamically to maximise profits. 1
Research Statement
"... My field of research is Theoretical Computer Science. My focus has been in the classical and quantum complexity of Boolean functions (including property testing, sensitivity and block sensitivity of Boolean functions and quantum database search), in electronic commerce, in graph algorithms and in co ..."
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My field of research is Theoretical Computer Science. My focus has been in the classical and quantum complexity of Boolean functions (including property testing, sensitivity and block sensitivity of Boolean functions and quantum database search), in electronic commerce, in graph algorithms and in coding theory. I have designed effective algorithms as well as proved lower bounds for the complexity of problems in this area. 1 Combinatorial Complexity Measures of Boolean Functions In my work in the field of combinatorial complexity measures of Boolean functions I strive to obtain a better understanding of different measures of hardness for Boolean functions, and their relation to the amount of resources needed to compute them in several combinatorial models. Previous results in the area have been obtained by insightful identification of the right measures of complexity and the choice of appropriate mathematical tools. Similarly, in my study I apply mathematical ideas and develop tools for analyzing the complexity of Boolean functions. 1.1 Property Testing Many data sets that arise in the fields of biology, geology, astronomy, climatology, artificial intelligence, etc are massive. In fact they are so huge that even reading the whole data requires impossibly large resources.