A multi-demand negotiation model based on fuzzy rules elicited via psychological experiments

This paper proposes a multi-demand negotiation model that takes the effect of human users’ psychological characteristics into consideration. Specifically, in our model each negotiating agent's preference over its demands can be changed, according to human users’ attitudes to risk, patience and regret, during the course of a negotiation. And the change of preference structures is determined by fuzzy logic rules, which are elicited through our psychological experiments. The applicability of our model is illustrated by using our model to solve a problem of political negotiation between two countries. Moreover, we do lots of theoretical and empirical analyses to reveal some insights into our model. In addition, to compare our model with existing ones, we make a survey on fuzzy logic based negotiation, and discuss the similarities and differences between our negotiation model and various consensus models

Out-of-equilibrium economic dynamics and persistent polarisation

Most of economics is equilibrium economics of one sort or another. The study of outof- equilibrium economics has largely been neglected. This thesis, engaging with ideas and techniques from complexity science, develops frameworks and tools for out-of-equilibrium modelling. We initially focus our attention on models of exchange before examining methods of agent-based modelling. Finally we look at a set of models for social dynamics with nontrivial micro-macro interrelationships. Chapter 2 introduces complexity science and relevant economic concepts. In particular we examine the idea of complex adaptive systems, the application of complexity to economics, some key ideas from microeconomics, agent-based modelling and models of segregation and/or polarisation. Chapter 3 develops an out-of-equilibrium, fully decentralised model of bilateral exchange. Initially we study the limiting properties of our out-of-equilibrium dynamic, characterising the conditions required for convergence to pairwise and Pareto optimal allocation sets. We illustrate problems that can arise for a rigid version of the model and show how even a small amount of experimentation can overcome these. We investigate the model numerically characterising the speed of convergence and changes in ex post wealth. In chapter 4 we now explicitly model the trading structure on a network. We derive analytical results for this general network case. We investigate the e�ect of network structure on outcomes numerically and contrast the results with the fully connected case of chapter 3. We look at extensions of the model including a version with an endogenous network structure and a versions where agents can learn to accept a `worthless' but widely available good in exchanges. Chapter 5 outlines and demonstrates a new approach to agent-based modelling which draws on a number techniques from contemporary software engineering. We develop a prototype framework to illustrate how the ideas might be applied in practice in order to address methodological gaps in many current approaches. We develop example agent-based models and contrast the approach with existing agent-based modelling approaches and the kind of purpose built models which were used for the numerical results in chapters 3 and 4. Chapter 6 develops a new set of models for thinking about a wide range of social dynamics issues including human capital acquisition and migration. We analyse the models initially from a Nash equilibrium perspective. Both continuum and �nite versions of the model are developed and related. Using the criterion of stochastic stability we think about the long run behaviour of a version of the model. We introduce agent heterogeneity into the model. We conclude with a fully dynamic version of the model (using techniques from chapter 5) which looks at endogenous segregation

Online Auctions

The economic literature on online auctions is rapidly growing because of the enormous amount of freely available field data. Moreover, numerous innovations in auction-design features on platforms such as eBay have created excellent research opportunities. In this article, we survey the theoretical, empirical, and experimental research on bidder strategies (including the timing of bids and winner's-curse effects) and seller strategies (including reserve-price policies and the use of buy-now options) in online auctions, as well as some of the literature dealing with online-auction design (including stopping rules and multi-object pricing rules).

Persuasion, Political Warfare, and Deterrence: Behavioral and Behaviorally Robust Models

This dissertation examines game theory models in the context of persuasion and competition wherein decision-makers are not completely rational by considering two complementary threads of research. The first thread of research pertains to offensive and preemptively defensive behavioral models. Research in this thread makes three notable contributions. First, an offensive modeling framework is created to identify how an entity optimally influences a populace to take a desired course of action. Second, a defensive modeling framework is defined wherein a regulating entity takes action to bound the behavior of multiple adversaries simultaneously attempting to persuade a group of decision-makers. Third, an offensive influence modeling framework under conditions of ambiguity is developed in accordance with historical information limitations, and we demonstrate how it can be used to select a robust course of action on a specific, data-driven use case. The second thread of research pertains to behavioral and behaviorally robust approaches to deterrence. Research in this thread makes two notable contributions. First, we demonstrate the alternative insights behavioral game theory generates for the analysis of classic deterrence games, and explicate the rich analysis generated from its combined use with standard equilibrium models. Second, we define behaviorally robust models for an agent to use in a normal form game under varying forms of uncertainty in order to inform deterrence policy decisions

Essays in behavioural economics

This thesis analyses decision making through the lens of behavioural economics. The three essays within consider variants of adverse selection problems and psychological biases which can manifest from imperfections in an information structure. The predominant psychological theory is informed by the idea of bounded awareness; one’s tendency to make suboptimal decisions through overlooking important information. The first essay concerns the winner’s curse in bargaining. The second essay assesses bidding behaviour in an auction environment. The third essay considers disclosure decisions. The general findings are as follows: (i) Research on the winner’s curse grew significantly since 1980 and peaked in 2009. The seminal work of William Samuelson and Max Bazerman in 1985 extended the concept to a new domain of bilateral bargaining and inspired fifteen further experimental studies. I demonstrate that costless nonbinding signals complicate decision-making but that alternative forms of cheap talk do not statistically influence bidding strategies. Secondly, I show that individuals find it challenging to strategically avoid information, exhibiting difficulties in performing contingent reasoning in bargaining. (ii) Analysing bidding efficiencies in high stakes and competitive auctions, I find that 80% of thoroughbred foals sold realise negative returns. The scale of losses is amplified as winning bids increase. On average, once a winning bid increases above €20,000, the assets enter the domain of losses. Incompatible incentives between stakeholders and diversification strategies fail to explain the inefficiencies. Although multiple interpretations of the findings exist, the results are consistent with the winner’s curse hypothesis and incompatible with the idea of profit maximisation. (iii) Investigating the unravelling principle in the hospitality industry, I find that the strict equilibrium prediction does not occur. A partial unravelling result is reported. The major finding is that a downward linear relationship exists between TripAdvisor signals and voluntary disclosures by hotels. Low ranked hotels tend to hide ratings information. Higher rank hotels are more likely to make a voluntary disclosure when compared to the lowest ranked. This raises ethical questions if consumers have psychological blind spots

Evolving game theory based decision making systems for NETA power market modelling, analysis and trading strategy development

In this thesis, current work carried out on analyzing the strategic behaviours in electricity trading is first reviewed. An intelligent decision-making and support technique, game theory, is often used in the market practice. Game theory is a discipline concerned with how individuals make decisions when they are partly aware of how their action might affect each other and when each individual might take this into account. Deficiencies and limitations of traditional game theory based methods developed for decision-making in electricity trading are also investigated. This research then explores to discover the impact of intelligent systems based trading strategies in the UK power markets. To model these behaviours and the New Electricity Trading Arrangements (NETA) system of the UK, traditional competitive and cooperative game theory strategies are taken into account in the work reported in this thesis. An improved methodology, “trigger price strategy”, is introduced to simulate power generation companies’ enhanced gaming strategies. Such modelling problem is, however, intractable and hence an extra-numerical search technique, Evolutionary Computation, is employed to solve the game theory based system modelling problem. An encoded Genetic Algorithm based technique is developed to search for an effective model for the complex decision-making process and to help decision-makers evaluate their strategies and bidding parameters. A novel and effective electricity trading simulation model is thus developed, where its design features are close to the NETA. The model scale is as close as possible to NETA. A complex and more realistic two-sided transaction mechanism with demand fully incorporated is incorporated in this model. These are a world first in this research area