Michael Harré
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View article: Decision, Inference, and Information: Formal Equivalences Under Active Inference
Decision, Inference, and Information: Formal Equivalences Under Active Inference Open
A central challenge in artificial intelligence and cognitive science is identifying a unifying principle that governs inference, learning, and action. Active inference proposes such a principle: the minimization of variational free energy.…
View article: Stylized Facts of High-Frequency Bitcoin Time Series
Stylized Facts of High-Frequency Bitcoin Time Series Open
This paper analyzes high-frequency intraday Bitcoin data from 2019 to 2022. The Bitcoin market index exhibits two distinct periods, characterized by abrupt volatility shifts. Bitcoin returns can be described by anomalous diffusion processe…
View article: Biological arrow of time: emergence of tangled information hierarchies and self-modelling dynamics
Biological arrow of time: emergence of tangled information hierarchies and self-modelling dynamics Open
We study open-ended evolution by focusing on computational and information-processing dynamics underlying major evolutionary transitions. In doing so, we consider biological organisms as hierarchical dynamical systems that generate regular…
View article: Artificial Theory of Mind and Self-Guided Social Organisation
Artificial Theory of Mind and Self-Guided Social Organisation Open
One of the challenges artificial intelligence (AI) faces is how a collection of agents coordinate their behaviour to achieve goals that are not reachable by any single agent. In a recent article by Ozmen et al this was framed as one of six…
View article: An AI Theory of Mind Will Enhance Our Collective Intelligence
An AI Theory of Mind Will Enhance Our Collective Intelligence Open
Collective intelligence plays a central role in many fields, from economics and evolutionary theory to neural networks and eusocial insects, and is also core to work on emergence and self-organisation in complex-systems theory. However, in…
View article: Factorised Active Inference for Strategic Multi-Agent Interactions
Factorised Active Inference for Strategic Multi-Agent Interactions Open
Understanding how individual agents make strategic decisions within collectives is important for advancing fields as diverse as economics, neuroscience, and multi-agent systems. Two complementary approaches can be integrated to this end. T…
View article: Biological arrow of time: Emergence of tangled information hierarchies and self-modelling dynamics
Biological arrow of time: Emergence of tangled information hierarchies and self-modelling dynamics Open
We study open-ended evolution by focusing on computational and information-processing dynamics underlying major evolutionary transitions. In doing so, we consider biological organisms as hierarchical dynamical systems that generate regular…
View article: Comparative analysis of stationarity for Bitcoin and the S&P500
Comparative analysis of stationarity for Bitcoin and the S&P500 Open
This paper compares and contrasts stationarity between the conventional stock market and cryptocurrency. The dataset used for the analysis is the intraday price indices of the S&P500 from 1996 to 2023 and the intraday Bitcoin indices from …
View article: Mathematica code for the topological analysis of Thom’s Catastrophes in 2 × 2 economic games
Mathematica code for the topological analysis of Thom’s Catastrophes in 2 × 2 economic games Open
René Thom's work on topological instabilities applied new methods to questions of dynamical stability that traditionally belonged to the domain of dynamical systems theorists. Topological instability focuses on universal properties of bifu…
View article: Stylized Facts of High-Frequency Bitcoin Time Series
Stylized Facts of High-Frequency Bitcoin Time Series Open
This paper analyses the high-frequency intraday Bitcoin dataset from 2019 to 2022. During this time frame, the Bitcoin market index exhibited two distinct periods, 2019-20 and 2021-22, characterized by an abrupt change in volatility. The B…
View article: Testing Game Theory of Mind Models for Artificial Intelligence
Testing Game Theory of Mind Models for Artificial Intelligence Open
In this article, we investigate the relative performance of artificial neural networks and structural models of decision theory by training 69 artificial intelligence models on a dataset of 7080 human decisions in extensive form games. The…
View article: Inverse Reinforcement Learning as the Algorithmic Basis for Theory of Mind: Current Methods and Open Problems
Inverse Reinforcement Learning as the Algorithmic Basis for Theory of Mind: Current Methods and Open Problems Open
Theory of mind (ToM) is the psychological construct by which we model another’s internal mental states. Through ToM, we adjust our own behaviour to best suit a social context, and therefore it is essential to our everyday interactions with…
View article: What Can Game Theory Tell Us about an AI ‘Theory of Mind’?
What Can Game Theory Tell Us about an AI ‘Theory of Mind’? Open
Game theory includes a rich source of methods for analysing strategic interactions where there are a small number of agents, each having only a few choices. In more complex settings though, where there are many choices over indefinite time…
View article: Entropy, Economics, and Criticality
Entropy, Economics, and Criticality Open
Information theory is a well-established method for the study of many phenomena and more than 70 years after Claude Shannon first described it in A Mathematical Theory of Communication it has been extended well beyond Shannon’s initial vis…
View article: Complexity Economics in a Time of Crisis: Heterogeneous Agents, Interconnections, and Contagion
Complexity Economics in a Time of Crisis: Heterogeneous Agents, Interconnections, and Contagion Open
In this article, we consider a variety of different mechanisms through which crises such as COVID-19 can propagate from the micro-economic behaviour of individual agents through to an economy’s aggregate dynamics and subsequently spill ove…
View article: Information Theory for Agents in Artificial Intelligence, Psychology, and Economics
Information Theory for Agents in Artificial Intelligence, Psychology, and Economics Open
This review looks at some of the central relationships between artificial intelligence, psychology, and economics through the lens of information theory, specifically focusing on formal models of decision-theory. In doing so we look at a p…
View article: The Polycentric Dynamics of Melbourne and Sydney: suburb attractiveness divides a city at the home ownership level
The Polycentric Dynamics of Melbourne and Sydney: suburb attractiveness divides a city at the home ownership level Open
Urban dynamics in large metropolitan areas result from complex interactions across social, economic and political factors, including population distribution, flows of wealth and infrastructure requirements. We develop a Census-calibrated m…
View article: The impact of social influence in Australian real-estate: market forecasting with a spatial agent-based model
The impact of social influence in Australian real-estate: market forecasting with a spatial agent-based model Open
Housing markets are inherently spatial, yet many existing models fail to capture this spatial dimension. Here we introduce a new graph-based approach for incorporating a spatial component in a large-scale urban housing agent-based model (A…
View article: Explaining herding and volatility in the cyclical price dynamics of\n urban housing markets using a large scale agent-based model
Explaining herding and volatility in the cyclical price dynamics of\n urban housing markets using a large scale agent-based model Open
Urban housing markets, along with markets of other assets, universally\nexhibit periods of strong price increases followed by sharp corrections. The\nmechanisms generating such non-linearities are not yet well understood. We\ndevelop an ag…
View article: Stationarity of the detrended time series of S&P500
Stationarity of the detrended time series of S&P500 Open
Our study presents the analysis of stock market data of S&P500 before and after been detrended. The analysis is based on two types of returns, simple return and log-return respectively. Both of them are non-stationary time series. This mea…
View article: Stationarity of the detrended price return in stock markets
Stationarity of the detrended price return in stock markets Open
This paper proposes a governing equation for stock market indexes that accounts for non-stationary effects. This is a linear Fokker-Planck equation (FPE) that describes the time evolution of the probability distribution function (PDF) of t…
View article: Singularities and Catastrophes in Economics: Historical Perspectives and\n Future Directions
Singularities and Catastrophes in Economics: Historical Perspectives and\n Future Directions Open
Economic theory is a mathematically rich field in which there are\nopportunities for the formal analysis of singularities and catastrophes. This\narticle looks at the historical context of singularities through the work of\ntwo eminent Fre…
View article: Singularities and Catastrophes in Economics: Historical Perspectives and Future Directions
Singularities and Catastrophes in Economics: Historical Perspectives and Future Directions Open
Economic theory is a mathematically rich field in which there are opportunities for the formal analysis of singularities and catastrophes. This article looks at the historical context of singularities through the work of two eminent French…
View article: Q-Gaussian diffusion in stock markets
Q-Gaussian diffusion in stock markets Open
We analyze the Standard & Poor's 500 stock market index from the last 22 years. The probability density function of price returns exhibits two well-distinguished regimes with self-similar structure: the first one displays strong super-diff…