86 research outputs found
Strategic decision-making in multi-agent markets: The emergence of endogenous crises and volatility
Traditional economic frameworks are built upon perfectly rational agents and equilibrium outcomes. However, during times of crises, these frameworks prove insufficient. In this thesis, we take an alternative perspective based on "Complexity Economics", relaxing the assumption of perfectly rational agents and allowing for out-of-equilibrium dynamics. While many contemporary approaches explain crises and non-equilibrium market phenomena as the rational reaction to external news, the emergence of endogenous crises remains an open question.
We begin addressing this question by demonstrating how a multi-agent model of heterogeneous boundedly rational agents acting according to heuristics can reproduce and forecast key non-linear price movements in the Australian housing market, during boom and bust cycles. In order to provide foundations for such heuristic-based reasoning, we then propose a novel information-theoretic approach, Quantal Hierarchy, for modelling limitations in strategic reasoning, demonstrating how this convincingly and generically captures the decision-making of interacting agents in competitive markets outperforming existing approaches. In addition, we demonstrate how a concise generalised market model can generate important stylised facts, such as fat-tails and volatility clustering, and allow for the emergence of crises, purely endogenously. This thesis provides support to the interacting agent hypothesis, addressing a crucial question of whether crisis emergence and various stylised facts can be seen as endogenous phenomena, and provides a generic method for representing strategic agent reasoning
Crises and collective socio-economic phenomena: simple models and challenges
Financial and economic history is strewn with bubbles and crashes, booms and
busts, crises and upheavals of all sorts. Understanding the origin of these
events is arguably one of the most important problems in economic theory. In
this paper, we review recent efforts to include heterogeneities and
interactions in models of decision. We argue that the Random Field Ising model
(RFIM) indeed provides a unifying framework to account for many collective
socio-economic phenomena that lead to sudden ruptures and crises. We discuss
different models that can capture potentially destabilising self-referential
feedback loops, induced either by herding, i.e. reference to peers, or
trending, i.e. reference to the past, and account for some of the phenomenology
missing in the standard models. We discuss some empirically testable
predictions of these models, for example robust signatures of RFIM-like herding
effects, or the logarithmic decay of spatial correlations of voting patterns.
One of the most striking result, inspired by statistical physics methods, is
that Adam Smith's invisible hand can badly fail at solving simple coordination
problems. We also insist on the issue of time-scales, that can be extremely
long in some cases, and prevent socially optimal equilibria to be reached. As a
theoretical challenge, the study of so-called "detailed-balance" violating
decision rules is needed to decide whether conclusions based on current models
(that all assume detailed-balance) are indeed robust and generic.Comment: Review paper accepted for a special issue of J Stat Phys; several
minor improvements along reviewers' comment
Collective behaviour in binary games with memory
Cyclic dynamics are displayed in many social, economic, physical and biological systems governed by negative frequency-dependent selection and delayed feedback. Here, I study the emergence and collapse of cyclic dynamics in an anti-coordination binary game with memory. In this model, individuals are faced with two options and aim to choose the option adopted by a minority in the group. Between adaptation moves, individuals learn about the behaviour of others by attending to and recollecting their choices. I introduce a novel double-fold definition of individual memory, incorporating a rate of observation (how often one collects new information) and duration (how long one remembers information). In the context of bounded rationality, these parameters mirror limitations due to cognitive and environmental constraints.
I show that finite and infinite observation rates generate different collective dynamics. In the limit of an infinite rate, the population exhibits deterministic and thus cyclic dynamics. In contrast, finite rates generate noise, enriching the game dynamics with different equilibria. The time evolution of the frequency of play of the two options in the group is investigated theoretically and computationally, and characterized as a function of the system parameters, particularly in terms of amplitude and period. The onset, decay and robustness of cyclic behaviour is discussed. To make this more concrete, the dynamics at play are illustrated with a specific example from fashion, intended as a sociological subject with collective and individual dynamics and imitation and distinction motifs. Applications to a number of other social, economic and biological contexts are also discussed
Supporting cooperation and coordination in open multi-agent systems
Cooperation and coordination between agents are fundamental processes for increasing
aggregate and individual benefit in open Multi-Agent Systems (MAS).
The increased ubiquity, size, and complexity of open MAS in the modern world
has prompted significant research interest in the mechanisms that underlie cooperative
and coordinated behaviour. In open MAS, in which agents join and
leave freely, we can assume the following properties: (i) there are no centralised
authorities, (ii) agent authority is uniform, (iii) agents may be heterogeneously
owned and designed, and may consequently have con
icting intentions and inconsistent
capabilities, and (iv) agents are constrained in interactions by a complex
connecting network topology. Developing mechanisms to support cooperative
and coordinated behaviour that remain effective under these assumptions
remains an open research problem.
Two of the major mechanisms by which cooperative and coordinated behaviour
can be achieved are (i) trust and reputation, and (ii) norms and conventions.
Trust and reputation, which support cooperative and coordinated
behaviour through notions of reciprocity, are effective in protecting agents from
malicious or selfish individuals, but their capabilities can be affected by a lack of
information about potential partners and the impact of the underlying network structure. Regarding conventions and norms, there are still a wide variety of
open research problems, including: (i) manipulating which convention or norm
a population adopts, (ii) how to exploit knowledge of the underlying network
structure to improve mechanism efficacy, and (iii) how conventions might be
manipulated in the middle and latter stages of their lifecycle, when they have
become established and stable.
In this thesis, we address these issues and propose a number of techniques
and theoretical advancements that help ensure the robustness and efficiency
of these mechanisms in the context of open MAS, and demonstrate new techniques
for manipulating convention emergence in large, distributed populations.
Specfically, we (i) show that gossiping of reputation information can mitigate
the detrimental effects of incomplete information on trust and reputation and reduce
the impact of network structure, (ii) propose a new model of conventions
that accounts for limitations in existing theories, (iii) show how to manipulate
convention emergence using small groups of agents inserted by interested
parties, (iv) demonstrate how to learn which locations in a network have the
greatest capacity to in
uence which convention a population adopts, and (v)
show how conventions can be manipulated in the middle and latter stages of
the convention lifecycle
Evolutionary games on graphs
Game theory is one of the key paradigms behind many scientific disciplines
from biology to behavioral sciences to economics. In its evolutionary form and
especially when the interacting agents are linked in a specific social network
the underlying solution concepts and methods are very similar to those applied
in non-equilibrium statistical physics. This review gives a tutorial-type
overview of the field for physicists. The first three sections introduce the
necessary background in classical and evolutionary game theory from the basic
definitions to the most important results. The fourth section surveys the
topological complications implied by non-mean-field-type social network
structures in general. The last three sections discuss in detail the dynamic
behavior of three prominent classes of models: the Prisoner's Dilemma, the
Rock-Scissors-Paper game, and Competing Associations. The major theme of the
review is in what sense and how the graph structure of interactions can modify
and enrich the picture of long term behavioral patterns emerging in
evolutionary games.Comment: Review, final version, 133 pages, 65 figure
Economics and the Complexity Vision: Chimerical Partners or Elysian Adventurers?
This work began as a review article of: "Complexity and the History of Economic Thought", edited by David Colander, Routledge, London,UK, 2000; & "The Complexity Vision and the Teaching of Economics", edited by David Colander, Edward Elgar, Cheltenham, UK, 2000. It has, in the writing, developed into my own vision of complexity economics
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