Browsing by Author "Dr. Michael Young, Committee Member"

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An Evolutionary Approach to Finding Bidding Strategies in a Combinatorial Auction
(2002-07-15) Phadke, Priti; Dr. Michael Young, Committee Member; Dr. Peter Wurman, Committee Chair; Dr. Jon Doyle, Committee Member
Auctions involve trading of variety of different items. Auctions that allow agents to bid for combinations of items are called Combinatorial Auctions (CAs). The Ascending k-Bundle Auction(AkBA) is a combinatorial auction founded on a notion of bundle price equilibrium. The purpose of this research is to explore the strategy space and help agents evolve strategies for a Proxy version of A1BA(P-AkBA). We use a Genetic algorithm to search the space of strategies. Several experiments were performed for different categories of problems and the resultsshow that the approach yields good solutions. We compare the outcomes of the evolved solutions with the outcomes that result from truthful bidding, and compare prices against those generated in the sealed-bid version of k-bundle auction and the standard GVA payments. We also make several observations about the effect of genetic parameters on the performance of search.
Image Processing for Cognitive Models in Dynamic Gaming Environments
(2003-07-07) Shah, Kunal Deepak; Dr. Robert St. Amant, Committee Chair; Dr. Michael Young, Committee Member; Dr. Munindar Singh, Committee Member
Cognitive models have typically dealt with environments that are either artificial or real but too simplistic. This stems from the fact that the process of describing the environment to the cognitive model is a complex vision problem. In order to realize the full potential of cognitive models, it is imperative that they be able to operate in natural domains. We attempt to overcome this limitation by providing a perceptual component to a cognitive model that interacts with more realistic environments. This perceptual component is an image processing substrate that has been customized for two different gaming environments. The substrate formerly worked only for the static environments we associate with conventional graphical user interfaces; the work we describe here extends its functionality to a more general class of interfaces, as represented by the driving game and Mars rover game. A cognitive model built on the ACT-R cognitive architecture has been developed that demonstrates the use of the image processing substrate in performing the driving task.
A Simple Auction for Early Delivery of High-Demand Products
(2004-11-01) Korrapati, Sameer; Dr. Michael Young, Committee Member; Dr. Munindar Singh, Committee Member; Dr. Peter Wurman, Committee Chair
Companies face an important challenge in deciding the allocation and pricing of high-demand products when they can supply them only in limited quantities, especially during initial releases. Instead of traditional means, letting free market mechanisms like auctions solve this problem can lead to more efficient outcomes. The Generalized Vickrey Auction (GVA) occupies a prominent place in auction theory because of its allocative efficiency and incentive properties. But implementing the GVA requires the auctioneer to solve n + 1 optimization problems, where n is the number of bidders. Moreover, it also requires complete information revelation by bidders, which can be a severe constraint in a real world application. Iterative auctions have been identified as a good alternative for practical implementations, though sometimes trading practicality with efficiency. We present a simple iterative auction that lets companies efficiently price and allocate limited quantities of high-demand goods. Self-interested and myopic agents can participate in a distributed manner in this online auction. We consider a supply of multiple units of heterogeneous goods under unit demand by agents that have private valuations. Because of its iterative nature, our auction computes the efficient outcome with very little information revelation from the agents. We show that this outcome is efficient and has incentive compatibility properties, like the GVA, under certain assumptions about the agent valuations. Our simulations have shown that the mechanism converges quickly to the equilibrium and collects relatively little information from the agents.
System Protection for Power Electronic Building Block Based DC Distribution Systems
(2004-12-07) Mahajan, Nikhil Ravindra; Dr. Mesut E Baran, Committee Chair; Dr. John J Grainger, Committee Member; Dr. Arthur W Kelley, Committee Member; Dr. Michael Young, Committee Member
The purpose of this research has been to develop an agent based protection and reconfiguration scheme for power electronic building block based (PEBB) DC distribution systems. One of the foremost applications would be in the new zonal DC distribution on naval ships. The research involves the design of an agent based protection scheme which uses the PEBBs for current limiting and circuit breaking purposes. Considerations are given to reduce the system downtime under fault conditions, allow proper coordination and provide backup protection. The research also involves the design of a reconfiguration management scheme based on collaborative agents. The collaboration ensures that the reconfiguration is achieved at a global level, enhancing the system survivability under the conditions of multiple faults and damages. The coordination ensures that only the faulted part of the system is isolated and the reconfiguration makes sure that the power to the healthy part of the system is supplied continuously. The reconfiguration management also performs load shedding if the generation does not meet the load demand of the reconfigured system due to a fault or damage in the generator.
Techniques For Finding Nash Equilibria In Combinatorial Auctions
(2005-07-07) Sureka, Ashish; Dr. Peter Wurman, Committee Chair; Dr. Munindar Singh, Committee Member; Dr. Michael Young, Committee Member; Dr. David Thuente, Committee Member
Auctions that allow participants to bid on a combination of items rather than just the individual items are called combinatorial auctions. For items that exhibit complementarity and substitutability, combinatorial auctions can be used to reach economically efficient allocations of goods and services. There has been a surge of recent research on combinatorial auctions because of the wide variety of practical situations to which they can be applied. There are several instances in which combinatorial auctions have already been applied to allocate scares resources, but there are still some challenging issues that need to be addressed before combinatorial auctions can be much more widely used in practice. Many different combinatorial auctions designs have been proposed by researchers and recently there has been a lot of work on studying the computational and strategic aspects of these auction designs. In this thesis, I analyze combinatorial auctions from a game theoretic perspective and propose techniques for determining pure strategy Nash equilibrium of combinatorial auctions. For a variety of reasons, combinatorial auctions pose serious computational challenges to compute Nash equilibria using current techniques. One problem is that the size of the strategy space in combinatorial auctions is very large and grows exponentially with the number of bidders and items. Another computational issue is that for combinatorial auctions it is computationally expensive to compute the payoffs of the players as a result of the joint actions. This makes it computationally expensive to determine the complete payoff matrix upfront and then determine Nash equilibrium. In this dissertation, we present techniques to overcome these problems. We present algorithms based on meta-heuristic search techniques, best response dynamics and linear programming to tackle these problems. We present empirical and theoretical results to support our claim that the algorithms perform well.
User Interface Softbots
(2003-12-11) Dudani, Ajay; Dr. Munindar Singh, Committee Member; Dr. Michael Young, Committee Member; Dr. Robert St. Amant, Committee Chair
A user interface softbot is a software agent that controls an interactive system through its graphical user interface, relying on visual information of the system rather than an application programming interfaces or access to source code. We have developed a prototype system that facilitates the use and extension of interface softbots, reforming the programming process and making it easier for new developers. We present the JSegMan substrate that facilitates the representation and identification of the conventional graphical user interface. The JSegMan substrate consists of sensors, effectors and framework for an agent that can control the user interface environment. Using image processing the sensor builds a representation of the desktop's visual interface. The effector module generates mouse and keyboard gestures to control the desktop environment. The sensor and effector modules work as eyes and hands of a controller application that can be tailored for a given application domain. We also present three applications - MSN Chatbots, the classical Blocks World problem solver and a GUI testing tool that use the JSegMan substrate and demonstrates applicability of JSegMan in use with off-the shelf applications, PDDL based planners and in testing environment respectively.