Using Agent-Based Simulation Models in the Analysis of Market Crashes

In this thesis we propose an agent-based model for a financial market with a single asset. The agents are motivated to trade via their personal beliefs about the future direction of the asset price moves. Additionally, the trades are restricted by the resources available to agents. The constructed model is used to attempt to gain some insight into the origin of large price moves in the market (“market crashes”). Monte Carlo simulations are used to study model behaviour under varying initial conditions. The model is found to be generally capable of reproducing the stylised facts of real financial markets. The ubiquity of relatively high incidence of large price moves in the results of model simulation, together with results from similar models by other authors allow us to conjecture that such moves are inherent in a market model based on a heterogenous population of intelligent agents. Finally, several directions for model improvement are identified

Being Interdisciplinary

In Being Interdisciplinary, Alan Wilson draws on five decades as a leading figure in urban science to set out a systems approach to interdisciplinarity for those conducting research in this and other fields. He argues that most research is interdisciplinary at base, and that a systems perspective is particularly appropriate for collaboration because it fosters an outlook that sees beyond disciplines. There is a more subtle thread, too. A systems approach enables researchers to identify the game-changers of the past as a basis for thinking outside convention, for learning how to do something new and how to be ambitious, in a nutshell how to be creative. Ultimately, the ideas presented address how to do research. Building on this systems focus, the book first establishes the basics of interdisciplinarity. Then, by drawing on the author’s experience of doing interdisciplinary research, and working from his personal toolkit, it offers general principles and a framework from which researchers can build their own interdisciplinary toolkit, with elements ranging from explorations of game-changers in research to superconcepts. In the last section, the book tackles questions of managing and organising research from individual to institutional scales. Alan Wilson deploys his wide experience – researcher in urban science, university professor and vice-chancellor, civil servant and institute director – to build the narrative. While his experience in urban science provides the illustrations, the principles apply across many research fields

Being Interdisciplinary: Adventures in urban science and beyond

In Being Interdisciplinary, Alan Wilson draws on five decades as a leading figure in urban science to set out a systems approach to interdisciplinarity for those conducting research in this and other fields. He argues that most research is interdisciplinary at base, and that a systems perspective is particularly appropriate for collaboration because it fosters an outlook that sees beyond disciplines. There is a more subtle thread, too. A systems approach enables researchers to identify the game-changers of the past as a basis for thinking outside convention, for learning how to do something new and how to be ambitious, in a nutshell how to be creative. Ultimately, the ideas presented address how to do research. Building on this systems focus, the book first establishes the basics of interdisciplinarity. Then, by drawing on the author’s experience of doing interdisciplinary research, and working from his personal toolkit, it offers general principles and a framework from which researchers can build their own interdisciplinary toolkit, with elements ranging from explorations of game-changers in research to superconcepts. In the last section, the book tackles questions of managing and organising research from individual to institutional scales. Alan Wilson deploys his wide experience – researcher in urban science, university professor and vice-chancellor, civil servant and institute director – to build the narrative. While his experience in urban science provides the illustrations, the principles apply across many research fields

Simulating social relations in multi-agent systems

Open distributed systems are comprised of a large number of heterogeneous nodes with disparate requirements and objectives, a number of which may not conform to the system specification. This thesis argues that activity in such systems can be regulated by using distributed mechanisms inspired by social science theories regarding similarity /kinship, trust, reputation, recommendation and economics. This makes it possible to create scalable and robust agent societies which can adapt to overcome structural impediments and provide inherent defence against malicious and incompetent action, without detriment to system functionality and performance. In particular this thesis describes: • an agent based simulation and animation platform (PreSage), which offers the agent developer and society designer a suite of powerful tools for creating, simulating and visualising agent societies from both a local and global perspective. • a social information dissemination system (SID) based on principles of self organisation which personalises recommendation and directs information dissemination. • a computational socio-cognitive and economic framework (CScEF) which integrates and extends socio-cognitive theories of trust, reputation and recommendation with basic economic theory. • results from two simulation studies investigating the performance of SID and the CScEF. The results show the production of a generic, reusable and scalable platform for developing and animating agent societies, and its contribution to the community as an open source tool. Secondly specific results, regarding the application of SID and CScEF, show that revealing outcomes of using socio-technical mechanisms to condition agent interactions can be demonstrated and identified by using Presage.Open Acces

Strategies for minority game and resource allocation.

She, Yingni.Thesis (M.Phil.)--Chinese University of Hong Kong, 2009.Includes bibliographical references (leaves 74-78).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Scope --- p.2Chapter 1.2 --- Motivation --- p.5Chapter 1.3 --- Structure of the Thesis --- p.6Chapter 2 --- Literature Review --- p.7Chapter 2.1 --- Intelligent Agents and Multiagent Systems --- p.8Chapter 2.1.1 --- Intelligent Agents --- p.8Chapter 2.1.2 --- Multiagent Systems --- p.10Chapter 2.2 --- Minority Game --- p.13Chapter 2.2.1 --- Minority Game --- p.13Chapter 2.2.2 --- Characteristics of Minority Game --- p.14Chapter 2.2.3 --- Strategies for Agents in Minority Game --- p.18Chapter 2.3 --- Resource Allocation --- p.22Chapter 2.3.1 --- Strategies for Agents in Multiagent Resource Allocation --- p.23Chapter 3 --- Individual Agent´ةs Wealth in Minority Game --- p.26Chapter 3.1 --- The Model --- p.26Chapter 3.2 --- Motivation --- p.27Chapter 3.3 --- Inefficiency Information --- p.28Chapter 3.4 --- An Intelligent Strategy --- p.31Chapter 3.5 --- Experiment Analysis --- p.32Chapter 3.6 --- Discussions and Analysis --- p.35Chapter 3.6.1 --- Equivalence to the Experience method --- p.36Chapter 3.6.2 --- Impact of M' and S' --- p.38Chapter 3.6.3 --- Impact of M and S --- p.41Chapter 3.6.4 --- Impact of Larger Number of Privileged Agents --- p.48Chapter 3.6.5 --- Comparisons with Related Work --- p.48Chapter 4 --- An Adaptive Strategy for Resource Allocation --- p.53Chapter 4.1 --- Problem Specification --- p.53Chapter 4.2 --- An Adaptive Strategy --- p.55Chapter 4.3 --- Remarks of the Adaptive Strategy --- p.57Chapter 4.4 --- Experiment Analysis --- p.58Chapter 4.4.1 --- Simulations --- p.58Chapter 4.4.2 --- Comparisons with Related Work --- p.62Chapter 5 --- Conclusions and Future Work --- p.69Chapter 5.1 --- Conclusions --- p.69Chapter 5.2 --- Future Work --- p.71A List of Publications --- p.73Bibliography --- p.7

Collective and Individual Rationality: Some Episodes in the History of Economic Thought

This thesis argues for the fundamental importance of the opposition between holistic and reductionistic world-views in economics. Both reductionism and holism may nevertheless underpin laissez-faire policy prescriptions. Scrutiny of the nature of the articulation between micro and macro levels in the writings of economists suggests that invisible hand theories play a key role in reconciling reductionist policy prescriptions with a holistic world. An examination of the prisoners' dilemma in game theory and Arrow's impossibility theorem in social choice theory sets the scene. The prisoners' dilemma epitomises the collective irrationality coordination problems lead to. The source of the dilemma is identified as the combination of interdependence in content and independence in form of the decision making process. Arrovian impossibility has been perceived as challenging traditional views of the relationship between micro and macro levels in economics. Conservative arguments against the possibility in principle of a social welfare function are criticised here as depending on an illicit dualism. The thesis then reviews the standpoints of Smith, Hayek and Keynes. For Smith, the social desirability of individual self-seeking activity is ensured by the 'invisible hand' of a god who has moulded us so to behave, that the quantity of happiness in the world is always maximised. Hayek seeks to re-establish the invisible hand in a secular age, replacing the agency of a deity with an evolutionary mechanism. Hayek's evolutionary theory, criticised here as being based on the exploded notion of group selection, cannot underpin the desirability of spontaneous outcomes. I conclude by arguing that Keynes shares the holistic approach of Smith and Hayek, but without their reliance on invisible hand mechanisms. If spontaneous processes cannot be relied upon to generate desirable social outcomes then we have to take responsibility for achieving this ourselves by establishing the appropriate institutional framework to eliminate macroeconomic prisoners' dilemmas

Strategies for selecting and evaluating information

Within the domain of psychology, Optimal Experimental Design (OED) principles have been used to model how people seek and evaluate information. Despite proving valuable as computational-level methods to account for people's behaviour, their descriptive and explanatory powers remain largely unexplored. In a series of experiments, we used a naturalistic crime investigation scenario to examine how people evaluate queries, as well as outcomes, in probabilistic contexts. We aimed to uncover the psychological strategies that people use, not just to assess whether they deviated from OED principles. In addition, we explored the adaptiveness of the identified strategies across both one-shot and stepwise information search tasks. We found that people do not always evaluate queries strictly in OED terms and use distinct strategies, such as by identifying a leading contender at the outset. Moreover, we identified aspects of zero-sum thinking and risk aversion that interact with people's information search strategies. Our findings have implications for building a descriptive account of information seeking and evaluation, accounting for factors that currently lie outside the realm of information-theoretic OED measures, such as context and the learner's own preferences

An Analysis of the Interaction Between Intelligent Software Agents and Human Users

Interactions between an intelligent software agent (ISA) and a human user are ubiquitous in everyday situations such as access to information, entertainment, and purchases. In such interactions, the ISA mediates the user’s access to the content, or controls some other aspect of the user experience, and is not designed to be neutral about outcomes of user choices. Like human users, ISAs are driven by goals, make autonomous decisions, and can learn from experience. Using ideas from bounded rationality (and deploying concepts from artificial intelligence, behavioural economics, control theory, and game theory), we frame these interactions as instances of an ISA whose reward depends on actions performed by the user. Such agents benefit by steering the user’s behaviour towards outcomes that maximise the ISA’s utility, which may or may not be aligned with that of the user. Video games, news recommendation aggregation engines, and fitness trackers can all be instances of this general case. Our analysis facilitates distinguishing various subcases of interaction (i.e. deception, coercion, trading, and nudging), as well as second-order effects that might include the possibility for adaptive interfaces to induce behavioural addiction, and/or change in user belief. We present these types of interaction within a conceptual framework, and review current examples of persuasive technologies and the issues that arise from their use. We argue that the nature of the feedback commonly used by learning agents to update their models and subsequent decisions could steer the behaviour of human users away from what benefits them, and in a direction that can undermine autonomy and cause further disparity between actions and goals as exemplified by addictive and compulsive behaviour. We discuss some of the ethical, social and legal implications of this technology and argue that it can sometimes exploit and reinforce weaknesses in human beings