The purpose of this thesis was to examine two works of science fiction by the Polish writer and satirist, Stanislaw Lem, which exemplify two broad philosophical themes central to his writings; viz., cosmology and personhood. In "The New Cosmogony," Lem focuses on the central problem of the philosophy of scientific cosmology, namely, what kind of explanation is-applicable to that science. Lem synthesizes religious and scientific views of the creation of the universe in his model of the cosmos as a Game of Civilizations with advanced technologies. Central to this work is the philosophical notion of intentionality. In "The Mask," Lem raises questions about personhood, consciousness, freedom, determinism, and responsibility by embedding them in the autobiographical narrative of a conscious, female machine. Lem's views on cosmology and his views on personhood both involve intentionality - the intentions of civilizations, on the one hand, and the intentions of a King and of the machine he created, on the other. Both works challenge all preconceptions about philosophy through the use of paradox, irony, and sometimes ridicule. Lem provides no answers, however. He is interested in setting up futuristic technological situations that are capable of undermining our basic assumptions about the world.

Market makers are unique entities in a market ecosystem. Unlike other participants that have exposure (either speculative or endogenous) to potential future states of the world, market making agents either endeavor to secure a risk-free profit or to facilitate trade that would otherwise not occur. In this thesis we present a principled theoretical framework for market making along with applications of that framework to different contexts. We begin by presenting a synthesis of two concepts—automated market making from the artificial intelligence literature and risk measures from the finance literature—that were developed independently. This synthesis implies that the market making agents we develop in this thesis also correspond to better ways of measuring the riskiness of a portfolio—an important application in quantitative finance. We then present the results of the Gates Hillman Prediction Market (GHPM), a fielded large-scale test of automated market making that successfully predicted the opening date of the new computer science buildings at CMU. Ranging over 365 possible opening days, the market’s large event partition required new advances like a novel span-based elicitation interface. The GHPM uncovered some practical flaws of automated market makers; we investigate how to rectify these failures by describing several classes of market makers that are better at facilitating trade in Internet prediction markets. We then shift our focus to notions of profit, and how a market maker can trade to maximize its own account. We explore applying our work to one of the largest and most heavily-traded markets in the world by recasting market making as an algorithmic options trading strategy. Finally, we investigate optimal market makers for fielding wagers when good priors are known, as in sports betting or insurance.

In order to succeed, it is imperative that all e-commerce systems include an effective and reliable trust and reputation modeling system. This is particularly true of decentralized e-commerce systems in which autonomous software engage in commercial transactions. Many researchers have sought to overcome the complexities of modeling a subjective, human concept like trust, resulting in several trust and reputation models. While these models each present a unique offering and solution to the problem, several issues persist. Most of the models require direct experience in the e-commerce system in order to make effective trust decisions. This leaves new agents and agents who only casually use the e-commerce system vulnerable. Additionally, the reputation ratings of agents who are relatively new to the system are often indistinguishable from scores for poorly performing agents. Finally, more tactics to defend against agents who exploit the characteristics of the open, distributed system for their own malicious needs are required. To address these issues, a new metric is devised and presented: seniority. Based on agent age and activity level within the e-commerce system, seniority provides a means of judging the credibility of other agents with little or no prior experience in the system. As the results of experimental analysis reveals, employing a reputation model that uses seniority provides considerable value to agents who are new agents, casual buyer agents and all other purchasing agents in the e-commerce system. This new metric therefore offers a significant contribution toward the development of enhanced and new trust and reputation models for deployment in real-world distributed e-commerce environments.

<p>Agent-based models (ABMs) are computational models used to simulate the behaviors, </p><p>actionsand interactions of agents within a system. The individual agents </p><p>each have their own set of assigned attributes and rules, which determine</p><p>their behavior within the ABM system. These rules can be</p><p>deterministic or probabilistic, allowing for a great deal of</p><p>flexibility. ABMs allow us to</p><p>observe how the behaviors of the individual agents affect the system</p><p>as a whole and if any emergent structure develops within the</p><p>system. Examining rule sets in conjunction with corresponding emergent</p><p>structure shows how small-scale changes can</p><p>affect large-scale outcomes within the system. Thus, we can better</p><p>understand and predict the development and evolution of systems of</p><p>interest. </p><p>ABMs have become ubiquitous---they used in business</p><p>(virtual auctions to select electronic ads for display), atomospheric</p><p>science (weather forecasting), and public health (to model epidemics).</p><p>But there is limited understanding of the statistical properties of</p><p>ABMs. Specifically, there are no formal procedures</p><p>for calculating confidence intervals on predictions, nor for</p><p>assessing goodness-of-fit, nor for testing whether a specific</p><p>parameter (rule) is needed in an ABM.</p><p>Motivated by important challenges of this sort, </p><p>this dissertation focuses on developing methodology for uncertainty</p><p>quantification and statistical inference in a likelihood-free context</p><p>for ABMs. </p><p>Chapter 2 of the thesis develops theory related to ABMs, </p><p>including procedures for model validation, assessing model </p><p>equivalence and measuring model complexity. </p><p>Chapters 3 and 4 of the thesis focuses on two approaches </p><p>for performing likelihood-free inference involving ABMs, </p><p>which is necessary because of the intractability of the </p><p>likelihood function due to the variety of input rules and </p><p>the complexity of outputs.</p><p>Chapter 3 explores the use of </p><p>Gaussian Process emulators in conjunction with ABMs to perform </p><p>statistical inference. This draws upon a wealth of research on emulators, </p><p>which find smooth functions on lower-dimensional Euclidean spaces that approximate</p><p>the ABM. Emulator methods combine observed data with output from ABM</p><p>simulations, using these</p><p>to fit and calibrate Gaussian-process approximations. </p><p>Chapter 4 discusses Approximate Bayesian Computation for ABM inference, </p><p>the goal of which is to obtain approximation of the posterior distribution </p><p>of some set of parameters given some observed data. </p><p>The final chapters of the thesis demonstrates the approaches </p><p>for inference in two applications. Chapter 5 presents application models the spread </p><p>of HIV based on detailed data on a social network of men who have sex with</p><p>men (MSM) in southern India. Use of an ABM</p><p>will allow us to determine which social/economic/policy </p><p>factors contribute to thetransmission of the disease. </p><p>We aim to estimate the effect that proposed medical interventions will</p><p>have on the spread of HIV in this community. </p><p>Chapter 6 examines the function of a heroin market </p><p>in the Denver, Colorado metropolitan area. Extending an ABM </p><p>developed from ethnographic research, we explore a procedure </p><p>for reducing the model, as well as estimating posterior </p><p>distributions of important quantities based on simulations.</p> / Dissertation

An argument for the compatibility of causal determinism and free will. Draws on recently conducted philosophical experimentation related to intuition and development of the intuition of agent-causal accounts of free will in children. Argues that regardless of the intuition held, the manner in which people arise to these intuitions shows that the working definition of free will is different than people posit. Lays groundwork for why the working definition of free will is compatible with causal determinism.

Corruption is a major cause and result of poverty around the globe. It arises at all levels of society, from national governments and military to small businesses and sports. Corruption affects all elements of society in some way as it undermines democracy and economic growth as well as the environment and people’s health. The main purpose of this thesis is to examine if corruption has a significant effect on economic growth in developing countries. The empirical analysis is conducted with a regression analysis, using data from recognized institutions. Other variables that can affect GDP per capita growth are also examined such as the level of democracy, fertility rate, life expectancy, education and the Initial GDP per capita to test for conditional convergence. In our main model, the empirical results show that corruption does not have a significant effect on economic growth but this is basically due to that the model exhibits multicollinearity. In our second model, where we omitted the variables Democracy, Initial GDP and Life expectancy, we found that corruption has a significant, negative effect on economic growth. This is in accordance with previous empirical results which hold that more corruption in a nation leads to less economic growth.

The principal-agent problem is an important model in the field of Economics of Information. In this thesis we study only a particular type of principal-agent problem which is called moral hazard model and by the principal-agent problem we mean it is moral hazard model. The moral hazard model actually belongs to the class of bilevel programming problems in Mathematics. In Economics. the first order approach is used to reduce the principal-agent problem to a single level optimization problem. However, this approach is only valid under some strong conditions. Moreover the approach can only be used under the assumption that the optimal action of the principal-agent problem and its relaxed problem appears only at an interior point. In this thesis, we consider a new relaxed problem. Under more general assumptions. we can solve the principal-agent problem without restricting the optimal action of the agent to be in the interior.

Managing public forestland is a challenging enterprise as the government must steward the actions of private forest companies while simultaneously considering public values, natural disturbance, markets, revenue generation and environmental services. Governments use timber sales, volume-based, and area-based tenures to delegate forest harvesting activities to individual timber companies. By delegating forest management, government must wisely navigate the principal-agent relationship to avoid unexpected outcomes. However, the agents’ response is often overlooked despite the likelihood that the agents may possess company-centric financial motivations. The British Columbia context, where the government is facing the aftermath of a catastrophic mountain pine beetle epidemic, provides a fruitful location for the study of the principal-agent dilemma. If forest companies share a future forest focus with the government, such that agents respond with actions that lead to the government’s first best outcome, the government could reduce policy analysis to an examination of the tradeoff between short-term revenue generation and sustainable differentiated product supply. But review of the silviculture funding mechanism reveals that the very regulatory mechanism used to achieve government’s results may affect the future forest estate by reducing the amount of salvage once the value of the forest is degraded below the cost to harvest and regenerate it. Relying primarily on harvest-based silviculture funding, the principal is shown to forego a 20 per cent increase in forest growth in the study area by not using the agents’ forestry expertise to improve the long term productive potential of the forest. A bi-level linear programming model is developed to merge the goals of government with the behavioural responses of the two predominant volume-based tenures used in BC. Results show that the government’s choice of harvest level, timber price and tenure instrument in recognition of agent response is the only way to achieve the government’s forest stewardship objective. Treating each element in isolation neglects the nature of the institutional system and will result not only in unintended outcomes, but very likely, policy failure. / Graduate

With the advancement of communication technology, more and more control processes happen in networked environment. This makes it possible for us to deploy multiple systems in a spatially distributed way such that they could finish certain tasks collaboratively. While it brings about numerous advantages over conventional control, challenges arise in the mean time due to the imperfection of communication. This thesis is aimed to solve some problems in cooperative control involving multiple agents in the presence of communication constraints. Overall, it is comprised of two main parts: Distributed consensus in multi-agent systems and bilateral teleoperation. Chapter 2 to Chapter 4 deal with the consensus problem in multi-agent systems. Our goal is to design appropriate control protocols such that the states of a group of agents will converge to a common value eventually. The robustness of multi-agent systems against various adverse factors in communication is our central concern. Chapter 5 copes with bilateral teleoperation with time delays. The task is to design control laws such that synchronization is reached between the master plant and slave plant. Meanwhile, transparency should be maintained within an acceptable level. Chapter 2 investigates the consensus problem in a multi-agent system with directed communication topology. The time delays are modeled as a Markov chain, thus more characteristics of delays are taken into account. A delay-dependent approach has been proposed to design the Laplacian matrix such that the system is robust against stochastic delays. The consensus problem is converted into stabilization of its equivalent error dynamics, and the mean square stability is employed to characterize its convergence property. One feature of Chapter 2 is redesign of the adjacency matrix, which makes it possible to adjust communication weights dynamically. In Chapter 3, average consensus in single-integrator agents with time-varying delays and random data losses is studied. The interaction topology is assumed to be undirected. The communication constraints lie in two aspects: 1) time-varying delays that are non-uniform and bounded; 2) data losses governed by Bernoulli processes with non-uniform probabilities. By considering the upper bounds of delays and probabilities of packet dropouts, sufficient conditions are developed to guarantee that the multi-agent system will achieve consensus. Chapter 4 is concerned with the consensus problem with double-integrator dynamics and non-uniform sampling. The communication topology is assumed to be fixed and directed. With the adoption of time-varying control gains and the theory on stochastic matrices, we prove that when the graph has a directed spanning tree and the control gains are properly selected, consensus will be reached. Chapter 5 deals with bilateral teleoperation with probabilistic time delays. The delays are from a finite set and each element in the set has a probability of occurrence. After defining the tracking error between the master and slave, the input-to-state stability is used to characterize the system performance. By taking into account the probabilistic information in time delays and using the pole placement technique, the teleoperation system has achieved better position tracking and enhanced transparency. / Graduate

Consensus is a central issue in designing multi-agent systems (MASs). How to design control protocols under certain communication topologies is the key for solving consensus problems. This thesis is focusing on investigating the consensus protocols under different scenarios: (1) The second-order system dynamics with Markov time delays; (2) The Euler-Lagrange dynamics with uniform and nonuniform sampling strategies and the event-based control strategy. Chapter 2 is focused on the consensus problem of the multi-agent systems with random delays governed by a Markov chain. For second-order dynamics under the sampled-data setting, we first convert the consensus problem to the stability analysis of the equivalent error system dynamics. By designing a suitable Lyapunov function and deriving a set of linear matrix inequalities (LMIs), we analyze the mean square stability of the error system dynamics with fixed communication topology. Since the transition probabilities in a Markov chain are sometimes partially unknown, we propose a method of estimating the delay for the next sampling time instant. We explicitly give a lower bound of the probability for the delay estimation which can ensure the stability of the error system dynamics. Finally, by applying an augmentation technique, we convert the error system dynamics to a delay-free stochastic system. A sufficient condition is established to guarantee the consensus of the networked multi-agent systems with switching topologies. Simulation studies for a fleet of unmanned vehicles verify the theoretical results. In Chapter 3, we propose the consensus control protocols involving both position and velocity information of the MASs with the linearized Euler-Lagrange dynamics, under uniform sampling and nonuniform sampling schemes, respectively. Then we extend the results to the case of applying the centralized event-triggered strategy, and accordingly analyze the consensus property. Simulation examples and comparisons verify the effectiveness of the proposed methods. / Graduate / 0548