Relevant bibliographies by topics / Quantal Response Equilibria

Academic literature on the topic 'Quantal Response Equilibria'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Quantal Response Equilibria"

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Blavatskyy, Pavlo. "A Refinement of Logit Quantal Response Equilibrium." International Game Theory Review 20, no. 02 (June 2018): 1850004. http://dx.doi.org/10.1142/s0219198918500044.

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Unlike the Nash equilibrium, logit quantal response equilibrium is affected by positive affine transformations of players’ von Neumann–Morgenstern utility payoffs. This paper presents a modification of a logit quantal response equilibrium that makes this equilibrium solution concept invariant to arbitrary normalization of utility payoffs. Our proposed modification can be viewed as a refinement of logit quantal response equilibria: instead of obtaining a continuum of equilibria (for different positive affine transformations of utility function) we now obtain only one equilibrium for all possible positive affine transformations of utility function. We define our refinement for simultaneous-move noncooperative games in the normal form.
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Turocy, Theodore L. "Computing sequential equilibria using agent quantal response equilibria." Economic Theory 42, no. 1 (February 6, 2009): 255–69. http://dx.doi.org/10.1007/s00199-009-0443-3.

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Voliotis, Dimitrios. "Strategic market games quantal response equilibria." Economic Theory 27, no. 2 (February 2006): 475–82. http://dx.doi.org/10.1007/s00199-004-0594-1.

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Golman, Russell. "Quantal response equilibria with heterogeneous agents." Journal of Economic Theory 146, no. 5 (September 2011): 2013–28. http://dx.doi.org/10.1016/j.jet.2011.06.007.

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McKelvey, Richard D., and Thomas R. Palfrey. "Quantal Response Equilibria for Normal Form Games." Games and Economic Behavior 10, no. 1 (July 1995): 6–38. http://dx.doi.org/10.1006/game.1995.1023.

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Goerg, Sebastian J., Abdolkarim Sadrieh, and Tibor Neugebauer. "Impulse Response Dynamics in Weakest Link Games." German Economic Review 17, no. 3 (August 1, 2016): 284–97. http://dx.doi.org/10.1111/geer.12100.

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Abstract In a recent paper, Croson et al. (2015) experimentally study three weakest link games with multiple symmetric equilibria. They demonstrate that static concepts based on the Nash equilibrium (including multiple Nash equilibria, quantal response equilibria, and equilibrium selection by risk and payoff dominance) cannot successfully capture the observed treatment differences. Using Reinhard Selten’s impulse response dynamics, we derive a proposition that provides a theoretical ranking of contribution levels in the weakest link games. We show that the predicted ranking of treatment outcomes is fully consistent with the observed data. In addition, we demonstrate that the impulse response dynamics perform well in tracking average contributions over time. We conclude that Reinhard Selten’s impulse response dynamics provide an extremely valuable behavioral approach that is not only capable of resolving the indecisiveness of static approaches in games with many equilibria, but that can also be used to track the development of choices over time in games with repeated interaction.
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Friedman, Evan. "Stochastic Equilibria: Noise in Actions or Beliefs?" American Economic Journal: Microeconomics 14, no. 1 (February 1, 2022): 94–142. http://dx.doi.org/10.1257/mic.20190013.

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We introduce noisy belief equilibrium (NBE) for normal-form games in which players best respond to noisy belief realizations. Axioms restrict belief distributions to be unbiased with respect to and responsive to changes in the opponents’ behavior. The axioms impose testable restrictions both within and across games, and we compare these restrictions to those of regular quantal response equilibrium (QRE) in which axioms are placed on the quantal response function as the primitive. NBE can generate similar predictions as QRE in several classes of games. Unlike QRE, NBE is a refinement of rationalizability and invariant to affine transformations of payoffs. (JEL C72, D83, D91)
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Wolpert, David H. "Trembling hand perfection for mixed quantal/best response equilibria." International Journal of Game Theory 38, no. 4 (July 28, 2009): 539–51. http://dx.doi.org/10.1007/s00182-009-0169-2.

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McKelvey, Richard D., and Thomas R. Palfrey. "Erratum to: Quantal response equilibria for extensive form games." Experimental Economics 18, no. 4 (October 23, 2015): 762–63. http://dx.doi.org/10.1007/s10683-015-9471-y.

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Tumennasan, Norovsambuu. "To err is human: Implementation in quantal response equilibria." Games and Economic Behavior 77, no. 1 (January 2013): 138–52. http://dx.doi.org/10.1016/j.geb.2012.10.004.

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Dissertations / Theses on the topic "Quantal Response Equilibria"

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Yi, Kang-Oh. "Three essays on quantal response equilibrium model /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 1999. http://wwwlib.umi.com/cr/ucsd/fullcit?p9938589.

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Elmgren, Rasmus, and Eric Blomquist. "Game Theory in Social Media with Quantal Response Equilibrium." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166441.

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This paper examines the possibility to construct a Game Theory model to describe Social Media with a Quantal Response Equilibrium. It is based on a literature study. The paper is influenced by "A Game-theoretic Model of Attention in Social Networks" written by Goel and Ronaghi but creates a more realistic model by replacing their Nash Equilibrium with a Quantal Response Equilibrium. Such model is constructed in the Result section and elaborated further in the Discussion. This paper also discusses the difficulties of Game Theory in Social Media and the flaws of the model created in the Result. The model helps provide an understanding of success in Social Media. It is possible to do continued research with more emphasis on the value of different players or how the order of content affects the level of attention.
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Blackwell, Keith. "Entropy Constrained Behavior in Financial Markets A Quantal Response Statistical Equilibrium Approach to Financial Modeling." Thesis, The New School, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10823347.

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Quantal Response Statistical Equilibrium (QRSE) models the joint probability distribution of asset returns and entropy constrained buy/sell decisions of investors and in doing so offers a behavioral foundation for many of the stylized facts we commonly observe in the distributions of asset returns and economic data such as fat-tails, excess peakedness, and skew. In a QRSE market model, investors condition the distribution of probabilistic buy/sell decisions on the extent to which investments offer above or below average returns. By modeling both returns and actions as probabilistic, QRSE is able to explain the marginal distributions of asset returns as the result of two opposing forces: 1) informational shocks that act as an underlying “natural” source of dispersion; 2) the tendency of investors to buy low/sell high that causes a mean-reversion dynamic, which decreases the entropy of the returns distribution we actually observe.

In this thesis, I introduce three new QRSE distributions each derived using the Maximum Entropy Principle. The first is a simple three parameter symmetric QRSE distribution that can fit and, therefore, provide a behavioral foundation for many commonly observed distributions including the Laplace, Gaussian, Logistic, and Student's T distributions. I then introduce a generalized maxent QRSE framework for expanding the assumptions of the basic model. I use this framework to derive two additional QRSE models that allow for skew: one that assumes skew is an implicit characteristic of the underlying data generating process and one that assumes that skew is due to asymmetric buy/sell preferences of investors. I also include two empirical applications. First, I apply QRSE to cross-sectional US equity returns. Second, I apply QRSE to 10 year US Treasury yields in a multiple equilibrium setting using a QRSE hidden Markov model.

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Schumacher, Tyler R. "Inequity-Averse Preferences in the Principal-Agent Framework." Miami University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=miami153299521737861.

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Ferecatu, Alina. "Three essays on biases in decision making." Thesis, Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales, 2014. http://www.theses.fr/2014ESEC0004.

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Cette thèse est organisée en trois chapitres. Chaque article analyse les déviations systématiques des décideurs par rapport aux prédictions économiques classiques dans certaines expériences bien connues. Les agents s’écartent de la voie optimale et explorent ou exploitent de manière excessive dans le problème du bandit manchot, ils exigent des taux d’intérêt bien plus élevés par rapport aux taux du marché financier afin de reporter leurs dépenses lorsqu’ils prennent des décisions de choix intertemporel, et ils ne se contentent pas de recevoir des petites sommes d’argent, même si, objectivement, ils devraient accepter cette offre, dans des expériences de négociation comme le jeu de l’ultimatum. Ces soi-disant «irrégularités» sont documentées dans les trois essais de thèse. Le essaies représentent une première étape afin de formuler des stratégies adaptées au profile psychologique de chaque individu, nécessaires pour surmonter les biais de décision
This dissertation is organized in three chapters. Each chapter analyzes decision makers’ systematic deviations from economic predictions in well-known experiments. People deviate from the optimal path and excessively explore or exploit in n-armed bandit games, demand interest rates well above financial market averages in order to defer consumption in intertemporal choice settings, and do not settle for receiving small amounts of money, even though they would be better off objectively, in bargaining games such as the ultimatum game. Such “irregularities” are documented in the three dissertation essays. The essays are intended as a first step to formulate individual specific, customized decision aids, useful to overcome such decision biases
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Östling, Robert. "Bounded rationality and endogenous preferences." Doctoral thesis, Handelshögskolan i Stockholm, Samhällsekonomi (S), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-454.

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(11038146), Daniel John Woods. "Essays on Experimental Economics." Thesis, 2021.

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This thesis contains three chapters, each of which covers a different topic in experimental economics.

The first chapter investigates power and power analysis in economics experiments. Power is the probability of detecting an effect when a true effect exists, which is an important but under-considered concept in empirical research. Power analysis is the process of selecting the number of observations in order to avoid issues with low power. However, it is often not clear ex-ante what the required parameters for a power analysis, like the effect size and standard deviation, should be.
This chapter considers the use of Quantal Choice/Response (QR) simulations for ex-ante power analysis, as it maps related data-sets into predictions for novel environments.
The QR can also guide optimal design decisions, both ex-ante as well as ex-post for conceptual replication studies. This chapter demonstrates QR simulations on a wide variety of applications related to power analysis and experimental design.

The second chapter considers a question of interest to computer scientists, information technology and security professionals. How do people distribute defenses over a directed network attack graph, where they must defend a critical node? Decision-makers are often subject to behavioral biases that cause them to make sub-optimal defense decisions. Non-linear probability weighting
is one bias that may lead to sub-optimal decision-making in this environment. An experimental test provides support for this conjecture, and also other empirically important biases such as naive diversification and preferences over the spatial timing of the revelation of an overall successful defense.

The third chapter analyzes how individuals resolve an exploration versus exploitation trade-off in a laboratory experiment. The experiment implements the single-agent exponential bandit model. The experiment finds that subjects respond in the predicted direction to changes in the prior belief, safe action, and discount factor. However, subjects also typically explore less than predicted. A structural model that incorporates risk preferences, base rate neglect/conservatism, and non-linear probability weighting explains the empirical findings well.
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(10996413), William J. Brown. "Essays on experimental group dynamics and competition." Thesis, 2021.

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This thesis consists of three chapters. In the first chapter, I investigate the effects of complexity in various voting systems on individual behavior in small group electoral competitions. Using a laboratory experiment, I observe individual behavior within one of three voting systems -- plurality, instant runoff voting (IRV), and score then automatic runoff (STAR). I then estimate subjects' behavior in three different models of bounded rationality. The estimated models are a model of Level-K thinking (Nagel, 1995), the Cognitive Hierarchy (CH) model (Camerer, et al. 2004), and a Quantal Response Equilibrium (QRE) (McKelvey and Palfrey 1995). I consistently find that more complex voting systems induce lower levels of strategic thinking. This implies that policy makers desiring more sincere voting behavior could potentially achieve this through voting systems with more complex strategy sets. Of the tested behavioral models, Level-K consistently fits observed data the best, implying subjects make decisions that combine of steps of thinking with random, utility maximizing, errors.

In the second chapter, I investigate the relationship between the mechanisms used to select leaders and both measures of group performance and leaders' ethical behavior. Using a laboratory experiment, we measure group performance in a group minimum effort task with a leader selected using one of three mechanisms: random, a competition task, and voting. After the group task, leaders must complete a task that asks them to behave honestly or dishonestly in questions related to the groups performance. We find that leaders have a large impact on group performance when compared to those groups without leaders. Evidence for which selection mechanism performs best in terms of group performance seems mixed. On measures of honesty, the strongest evidence seems to indicate that honesty is most positively impacted through a voting selection mechanism, which differences in ethical behavior between the random and competition selection treatments are negligible.


In the third chapter, I provide an investigation into the factors and conditions that drive "free riding" behavior in dynamic innovation contests. Starting from a dynamic innovation contest model from Halac, et al. (2017), I construct a two period dynamic innovation contest game. From there, I provide a theoretical background and derivation of mixed strategies that can be interpreted as an agent's degree to which they engage in free riding behavior, namely through allowing their opponent to exert effort in order to uncover information about an uncertain state of the world. I show certain conditions must be fulfilled in order to induce free riding in equilibrium, and also analytically show the impact of changing contest prize structures on the degree of free riding. I end this paper with an experimental design to test these various theoretical conclusions in a laboratory setting while also considering the behavioral observations recorded in studies investigating similar contest models and provide a plan to analyze the data collected by this laboratory experiment.

All data collected for this study consists of individual human subject data collected from laboratory experiments. Project procedures have been conducted in accordance with Purdue's internal review board approval and known consent from all participants was obtained.
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Books on the topic "Quantal Response Equilibria"

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Quantal Response Equilibrium. Princeton University Press, 2020.

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Goeree, Jacob K., Thomas R. Palfrey, and Charles A. Holt. Quantal Response Equilibrium: A Stochastic Theory of Games. Princeton University Press, 2016.

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Horing, Norman J. Morgenstern. Quantum Statistical Field Theory. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198791942.001.0001.

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The methods of coupled quantum field theory, which had great initial success in relativistic elementary particle physics and have subsequently played a major role in the extensive development of non-relativistic quantum many-particle theory and condensed matter physics, are at the core of this book. As an introduction to the subject, this presentation is intended to facilitate delivery of the material in an easily digestible form to students at a relatively early stage of their scientific development, specifically advanced undergraduates (rather than second or third year graduate students), who are mathematically strong physics majors. The mechanism to accomplish this is the early introduction of variational calculus with particle sources and the Schwinger Action Principle, accompanied by Green’s functions, and, in addition, a brief derivation of quantum mechanical ensemble theory introducing statistical thermodynamics. Important achievements of the theory in condensed matter and quantum statistical physics are reviewed in detail to help develop research capability. These include the derivation of coupled field Green’s function equations of motion for a model electron-hole-phonon system, extensive discussions of retarded, thermodynamic and non-equilibrium Green’s functions, and their associated spectral representations and approximation procedures. Phenomenology emerging in these discussions includes quantum plasma dynamic, nonlocal screening, plasmons, polaritons, linear electromagnetic response, excitons, polarons, phonons, magnetic Landau quantization, van der Waals interactions, chemisorption, etc. Considerable attention is also given to low-dimensional and nanostructured systems, including quantum wells, wires, dots and superlattices, as well as materials having exceptional conduction properties such as superconductors, superfluids and graphene.
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Tiwari, Sandip. Semiconductor Physics. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198759867.001.0001.

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A graduate-level text, Semiconductor physics: Principles, theory and nanoscale covers the central topics of the field, together with advanced topics related to the nanoscale and to quantum confinement, and integrates the understanding of important attributes that go beyond the conventional solid-state and statistical expositions. Topics include the behavior of electrons, phonons and photons; the energy and entropic foundations; bandstructures and their calculation; the behavior at surfaces and interfaces, including those of heterostructures and their heterojunctions; deep and shallow point perturbations; scattering and transport, including mesoscale behavior, using the evolution and dynamics of classical and quantum ensembles from a probabilistic viewpoint; energy transformations; light-matter interactions; the role of causality; the connections between the quantum and the macroscale that lead to linear responses and Onsager relationships; fluctuations and their connections to dissipation, noise and other attributes; stress and strain effects in semiconductors; properties of high permittivity dielectrics; and remote interaction processes. The final chapter discusses the special consequences of the principles to the variety of properties (consequences of selection rules, for example) under quantum-confined conditions and in monolayer semiconductor systems. The text also bring together short appendices discussing transform theorems integral to this study, the nature of random processes, oscillator strength, A and B coefficients and other topics important for understanding semiconductor behavior. The text brings the study of semiconductor physics to the same level as that of the advanced texts of solid state by focusing exclusively on the equilibrium and off-equilibrium behaviors important in semiconductors.
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Sethna, James P. Statistical Mechanics: Entropy, Order Parameters, and Complexity. 2nd ed. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198865247.001.0001.

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This text distills the core ideas of statistical mechanics to make room for new advances important to information theory, complexity, active matter, and dynamical systems. Chapters address random walks, equilibrium systems, entropy, free energies, quantum systems, calculation and computation, order parameters and topological defects, correlations and linear response theory, and abrupt and continuous phase transitions. Exercises explore the enormous range of phenomena where statistical mechanics provides essential insight — from card shuffling to how cells avoid errors when copying DNA, from the arrow of time to animal flocking behavior, from the onset of chaos to fingerprints. The text is aimed at graduates, undergraduates, and researchers in mathematics, computer science, engineering, biology, and the social sciences as well as to physicists, chemists, and astrophysicists. As such, it focuses on those issues common to all of these fields, background in quantum mechanics, thermodynamics, and advanced physics should not be needed, although scientific sophistication and interest will be important.
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Boothroyd, Andrew T. Principles of Neutron Scattering from Condensed Matter. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198862314.001.0001.

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The book contains a comprehensive account of the theory and application of neutron scattering for the study of the structure and dynamics of condensed matter. All the principal experimental techniques available at national and international neutron scattering facilities are covered. The formal theory is presented, and used to show how neutron scattering measurements give direct access to a variety of correlation and response functions which characterize the equilibrium properties of bulk matter. The determination of atomic arrangements and magnetic structures by neutron diffraction and neutron optical methods is described, including single-crystal and powder diffraction, diffuse scattering from disordered structures, total scattering, small-angle scattering, reflectometry, and imaging. The principles behind the main neutron spectroscopic techniques are explained, including continuous and time-of-flight inelastic scattering, quasielastic scattering, spin-echo spectroscopy, and Compton scattering. The scattering cross-sections for atomic vibrations in solids, diffusive motion in atomic and molecular fluids, and single-atom and cooperative magnetic excitations are calculated. A detailed account of neutron polarization analysis is given, together with examples of how polarized neutrons can be exploited to obtain information about structural and magnetic correlations which cannot be obtained by other methods. Alongside the theoretical aspects, the book also describes the essential practical information needed to perform experiments and to analyse and interpret the data. Exercises are included at the end of each chapter to consolidate and enhance understanding of the material, and a summary of relevant results from mathematics, quantum mechanics, and linear response theory, is given in the appendices.
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Book chapters on the topic "Quantal Response Equilibria"

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Goeree, Jacob K., Charles A. Holt, and Thomas R. Palfrey. "Quantal Response Equilibria." In The New Palgrave Dictionary of Economics, 11059–65. London: Palgrave Macmillan UK, 2018. http://dx.doi.org/10.1057/978-1-349-95189-5_2860.

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Goeree, Jacob K., Charles A. Holt, and Thomas R. Palfrey. "Quantal Response Equilibria." In The New Palgrave Dictionary of Economics, 1–8. London: Palgrave Macmillan UK, 2008. http://dx.doi.org/10.1057/978-1-349-95121-5_2432-1.

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Goeree, Jacob K., Charles A. Holt, and Thomas R. Palfrey. "Quantal Response Equilibria." In The New Palgrave Dictionary of Economics, 1–7. London: Palgrave Macmillan UK, 2013. http://dx.doi.org/10.1057/978-1-349-95121-5_2860-1.

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Goeree, Jacob K., Charles A. Holt, and Thomas R. Palfrey. "quantal response equilibria." In Behavioural and Experimental Economics, 234–42. London: Palgrave Macmillan UK, 2010. http://dx.doi.org/10.1057/9780230280786_29.

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McCubbins, Mathew D., Mark Turner, and Nicholas Weller. "Testing the Foundations of Quantal Response Equilibrium." In Social Computing, Behavioral-Cultural Modeling and Prediction, 144–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37210-0_16.

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Kirchner, Stefan, Farzaneh Zamani, and Enrique Muñoz. "Nonlinear Thermoelectric Response of Quantum Dots: Renormalized Dual Fermions Out of Equilibrium." In NATO Science for Peace and Security Series B: Physics and Biophysics, 129–68. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4984-9_10.

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Vitale, S., M. Cerdonio, G. A. Prodi, A. Cavalleri, P. Falferi, and A. Maraner. "Linear Response and Thermal Equilibrium Noise of Magnetic Materials at Low Temperature: Logarithmic Relaxation, 1/F Noise, Activation and Tunnelling." In Quantum Tunneling of Magnetization — QTM ’94, 157–69. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0403-6_9.

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Goeree, Jacob K., Charles A. Holt, and Thomas R. Palfrey. "Quantal Response Equilibrium in Extensive-Form Games." In Quantal Response Equilibrium. Princeton University Press, 2016. http://dx.doi.org/10.23943/princeton/9780691124230.003.0003.

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This chapter lays out the general theory of quantal response equilibrium (QRE) for extensive-form games. The formulation of the model is necessarily more complicated because timing and information now play a direct role in the decision maker's choice. This can have interesting and unanticipated consequences. It first describes four possible ways to define QRE in extensive-form games, depending on how the games are represented. It then turns to the structural agent quantal response equilibrium (AQRE) extensive-form games. This is followed by a discussion of the logit AQRE model, which implies a unique selection from the set of Nash equilibria. This selection is defined by the connected component of the logit AQRE correspondence. The final section presents an AQRE analysis of the centipede game.
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McKelvey, Richard D., and Thomas R. Palfrey. "Chapter 60 Quantal Response Equilibria: A Brief Synopsis." In Handbook of Experimental Economics Results, 541–48. Elsevier, 2008. http://dx.doi.org/10.1016/s1574-0722(07)00060-1.

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Goeree, Jacob K., Charles A. Holt, and Thomas R. Palfrey. "Dynamics and Learning." In Quantal Response Equilibrium. Princeton University Press, 2016. http://dx.doi.org/10.23943/princeton/9780691124230.003.0005.

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This chapter explores questions related to learning and dynamics. The first part explores dynamic quantal response equilibrium models where strategies are conditioned on observed histories of past decisions and outcomes of stage games. The second part considers models in which players are learning about others' behavior via a process in which they may update and respond to current beliefs in a noisy (quantal) manner. The final section explores learning models that involve quantal responses to beliefs formed by processing information from finite (but possibly long) histories of prior or observed action profiles. The formulation permits consideration of a wide variety of exogenous or even endogenous (e.g., least squares) learning rules.
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Conference papers on the topic "Quantal Response Equilibria"

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Golman, Russell. "Quantal response equilibria with heterogeneous agents." In the Behavioral and Quantitative Game Theory. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1807406.1807456.

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Friedman, Evan, and Felix Mauersberger. "Quantal Response Equilibrium with Symmetry." In EC '22: The 23rd ACM Conference on Economics and Computation. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3490486.3538351.

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Kozitsina, Tatiana, and Ivan Kozitsin. "Studying Negative Rationality in Quantal Response Equilibrium." In 2022 4th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA). IEEE, 2022. http://dx.doi.org/10.1109/summa57301.2022.9973908.

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Scharfenaker, Ellis. "Quantal Response Statistical Equilibrium: A New Class of Maximum Entropy Distributions." In Entropy 2021: The Scientific Tool of the 21st Century. Basel, Switzerland: MDPI, 2021. http://dx.doi.org/10.3390/entropy2021-09806.

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Cerny, Jakub, Viliam Lisý, Branislav Bošanský, and Bo An. "Dinkelbach-Type Algorithm for Computing Quantal Stackelberg Equilibrium." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/35.

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Stackelberg security games (SSGs) have been deployed in many real-world situations to optimally allocate scarce resource to protect targets against attackers. However, actual human attackers are not perfectly rational and there are several behavior models that attempt to predict subrational behavior. Quantal response is among the most commonly used such models and Quantal Stackelberg Equilibrium (QSE) describes the optimal strategy to commit to when facing a subrational opponent. Non-concavity makes computing QSE computationally challenging and while there exist algorithms for computing QSE for SSGs, they cannot be directly used for solving an arbitrary game in the normal form. We (1) present a transformation of the primal problem for computing QSE using a Dinkelbach's method for any general-sum normal-form game, (2) provide a gradient-based and a MILP-based algorithm, give the convergence criteria, and bound their error, and finally (3) we experimentally demonstrate that using our novel transformation, a QSE can be closely approximated several orders of magnitude faster.
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Ling, Chun Kai, Fei Fang, and J. Zico Kolter. "What Game Are We Playing? End-to-end Learning in Normal and Extensive Form Games." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/55.

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Although recent work in AI has made great progress in solving large, zero-sum, extensive-form games, the underlying assumption in most past work is that the parameters of the game itself are known to the agents. This paper deals with the relatively under-explored but equally important "inverse" setting, where the parameters of the underlying game are not known to all agents, but must be learned through observations. We propose a differentiable, end-to-end learning framework for addressing this task. In particular, we consider a regularized version of the game, equivalent to a particular form of quantal response equilibrium, and develop 1) a primal-dual Newton method for finding such equilibrium points in both normal and extensive form games; and 2) a backpropagation method that lets us analytically compute gradients of all relevant game parameters through the solution itself. This ultimately lets us learn the game by training in an end-to-end fashion, effectively by integrating a "differentiable game solver" into the loop of larger deep network architectures. We demonstrate the effectiveness of the learning method in several settings including poker and security game tasks.
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7

Musho, T. D., and D. G. Walker. "Coupled Non-Equilibrium Green’s Function (NEGF) Electron-Phonon Interaction in Thermoelectric Materials." In ASME 2011 International Mechanical Engineering Congress and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/imece2011-65786.

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Abstract:
Over the last decade, nano-structured materials have shown a promising avenue for enhancement of the thermoelectric figure of merit. These performance enhancements in most cases have been a direct result of selectively modifying certain geometric attributes that alter the thermal or electrical transport in a desirable fashion. More often, models used to study the electrical and/or thermal transport are calculated independent of each other. However, studies have suggested electrical and thermal transport are intimately linked at the nanoscale. This provides an argument for a more rigorous treatment of the physics in an effort to capture the response of both electrons and phonons simultaneously. A simulation method has been formulated to capture the electron-phonon interaction of nanoscale electronics through a coupled non-equilibrium Greens function (NEGF) method. This approach is unique because the NEGF electron solution and NEGF phonon solution have only been solved independently and have never been coupled to capture a self-consistent inelastic electron-phonon scattering. One key aspect of this formalism is that the electron and phonon description is derived from a quantum point of view and no correction terms are necessary to account for the probabilistic nature of the transport. Additionally, because the complete phonon description is solved, scattering rates of individual phonon frequencies can be investigated to determine how electron-phonon scattering of particular frequencies influences the transport. This computational method is applied to the study of Si/Ge nanostructured superlattice thermoelectric materials.
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