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Your search keyword '"Farmer, Doyne"' showing total 27 results
Start Over Author "Farmer, Doyne" Publication Year Range Last 50 years Publication Type Periodicals
27 results on '"Farmer, Doyne"'

1. Qualities, challenges and future of genetic algorithms: a literature review

Author

Vie, Aymeric, Kleinnijenhuis, Alissa M., and Farmer, Doyne J.

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Distributed, Parallel, and Cluster Computing, Mathematics - Optimization and Control
Abstract

Genetic algorithms, computer programs that simulate natural evolution, are increasingly applied across many disciplines. They have been used to solve various optimisation problems from neural network architecture search to strategic games, and to model phenomena of adaptation and learning. Expertise on the qualities and drawbacks of this technique is largely scattered across the literature or former, motivating an compilation of this knowledge at the light of the most recent developments of the field. In this review, we present genetic algorithms, their qualities, limitations and challenges, as well as some future development perspectives. Genetic algorithms are capable of exploring large and complex spaces of possible solutions, to quickly locate promising elements, and provide an adequate modelling tool to describe evolutionary systems, from games to economies. They however suffer from high computation costs, difficult parameter configuration, and crucial representation of the solutions. Recent developments such as GPU, parallel and quantum computing, conception of powerful parameter control methods, and novel approaches in representation strategies, may be keys to overcome those limitations. This compiling review aims at informing practitioners and newcomers in the field alike in their genetic algorithm research, and at outlining promising avenues for future research. It highlights the potential for interdisciplinary research associating genetic algorithms to pulse original discoveries in social sciences, open ended evolution, artificial life and AI., Comment: Early draft, feedback is welcome

Published
2020

2. Supply and demand shocks in the COVID-19 pandemic: An industry and occupation perspective

Author

del Rio-Chanona, R. Maria, Mealy, Penny, Pichler, Anton, Lafond, Francois, and Farmer, Doyne

Subjects
Economics - General Economics
Abstract

We provide quantitative predictions of first order supply and demand shocks for the U.S. economy associated with the COVID-19 pandemic at the level of individual occupations and industries. To analyze the supply shock, we classify industries as essential or non-essential and construct a Remote Labor Index, which measures the ability of different occupations to work from home. Demand shocks are based on a study of the likely effect of a severe influenza epidemic developed by the US Congressional Budget Office. Compared to the pre-COVID period, these shocks would threaten around 22% of the US economy's GDP, jeopardise 24% of jobs and reduce total wage income by 17%. At the industry level, sectors such as transport are likely to have output constrained by demand shocks, while sectors relating to manufacturing, mining and services are more likely to be constrained by supply shocks. Entertainment, restaurants and tourism face large supply and demand shocks. At the occupation level, we show that high-wage occupations are relatively immune from adverse supply and demand-side shocks, while low-wage occupations are much more vulnerable. We should emphasize that our results are only first-order shocks -- we expect them to be substantially amplified by feedback effects in the production network.

Published
2020
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3. Towards a taxonomy of learning dynamics in 2 x 2 games

Author

Pangallo, Marco, Sanders, James, Galla, Tobias, and Farmer, Doyne

Subjects
Economics - General Economics, Nonlinear Sciences - Chaotic Dynamics
Abstract

Do boundedly rational players learn to choose equilibrium strategies as they play a game repeatedly? A large literature in behavioral game theory has proposed and experimentally tested various learning algorithms, but a comparative analysis of their equilibrium convergence properties is lacking. In this paper we analyze Experience-Weighted Attraction (EWA), which generalizes fictitious play, best-response dynamics, reinforcement learning and also replicator dynamics. Studying $2\times 2$ games for tractability, we recover some well-known results in the limiting cases in which EWA reduces to the learning rules that it generalizes, but also obtain new results for other parameterizations. For example, we show that in coordination games EWA may only converge to the Pareto-efficient equilibrium, never reaching the Pareto-inefficient one; that in Prisoner Dilemma games it may converge to fixed points of mutual cooperation; and that limit cycles or chaotic dynamics may be more likely with longer or shorter memory of previous play.

Published
2017

4. A generative model for feedback networks

Author

White, Douglas R., Kejzar, Natasa, Tsallis, Constantino, Farmer, Doyne, and White, Scott

Subjects
Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Statistical Mechanics
Abstract

We investigate a simple generative model for network formation. The model is designed to describe the growth of networks of kinship, trading, corporate alliances, or autocatalytic chemical reactions, where feedback is an essential element of network growth. The underlying graphs in these situations grow via a competition between cycle formation and node addition. After choosing a given node, a search is made for another node at a suitable distance. If such a node is found, a link is added connecting this to the original node, and increasing the number of cycles in the graph; if such a node cannot be found, a new node is added, which is linked to the original node. We simulate this algorithm and find that we cannot reject the hypothesis that the empirical degree distribution is a q-exponential function, which has been used to model long-range processes in nonequilibrium statistical mechanics., Comment: 11 pages, 6 figures

Published
2005
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5. A generative model for feedback networks

Author

White, Douglas R, Kejzar, Natasa, Tsallis, Constantino, Farmer, Doyne, and White, Scott D.

Subjects
Social networks, simulation, generatibve model, feedback, nonextensive entropy, q-exponential
Abstract

We investigate a simple generative model for network formation. The model is designed to describe the growth of networks of kinship, trading, corporate alliances, or autocatalytic chemical reactions, where feedback is an essential element of network growth. The underlying graphs in these situations grow via a competition between cycle formation and node addition. After choosing a given node, a search is made for another node at a suitable distance. If such a node is found, a link is added connecting this to the original node, and increasing the number of cycles in the graph; if such a node cannot be found, a new node is added, which is linked to the original node. We simulate this algorithm and find that we cannot reject the hypothesis that the empirical degree distribution is a q-exponential function, which has been used to model long-range processes in nonequilibrium statistical mechanics.

Published
2005

6. Response

Author

Battiston, Stefano, Farmer, Doyne, Flache, Andreas, Garlaschelli, Diego, Haldane, Andy, Heesterbeek, Hans, Hommes, Cars, Jaeger, Carlo, May, Robert, and Scheffer, Marten

Published
2016

7. Intelligent Data Analysis of Intelligent Systems

Author

Krakauer, David C., Flack, Jessica C., Dedeo, Simon, Farmer, Doyne, Rockmore, Daniel, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Cohen, Paul R., editor, Adams, Niall M., editor, and Berthold, Michael R., editor

Published
2010
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13. Financial complexity: Accounting for fraud--Response

Author

Battiston, Stefano, Farmer, Doyne, Flache, Andreas, Garlaschelli, Diego, Haldane, Andy, Heesterbeek, Hans, Hommes, Cars, Jaeger, Carlo, May, Robert, Scheffer, Marten, Dep of Animals in Science and Society, Dep Gezondheidszorg Landbouwhuisdieren, LS Theoretische Epidemiologie, and dFAH I&I

Subjects
Taverne
Published
2016

14. EXPERIMENTAL MATHEMATICS: THE ROLE OF COMPUTATION IN NONLINEAR SCIENCE.

Author

Campbell, David, Crutchfield, Jim, Farmer, Doyne, and Jen, Erica

Subjects
COMPUTERS, NONLINEAR theories, MATHEMATICAL programming, COMPUTER architecture, MATHEMATICS problems & exercises, MATHEMATICAL physics
Abstract

The article discusses the role of computers in nonlinear science. The term experimental mathematics has been coined to describe computer-based investigations into nonlinear problems that are inaccessible to analytic methods. The experimental mathematician uses the computer to simulate the solutions of nonlinear equations and thereby to gain insights into their behavior and to suggest directions for future analytic research. Nonlinear science has become a discipline in itself, simply because nature is intrinsically nonlinear. The term nonlinear science, meaning the science of problems that are not linear, may seem odd at first. It seems to suggest that linear problems are the central issue, while in fact precisely the opposite is true. Although simple dynamical systems with low dimensional phase spaces can model much of the real world, the analysis of many physical phenomena requires a somewhat different approach. Digital computers, at both mainframe and minicomputer levels and in the conventional sequential or partially pipelined architecture, remain the general purpose tool of experimental mathematicians.

Published
1985
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19. What's evolving in artificial life

Author

Farmer, Doyne and Kauffman, Stuart

Subjects
Biological models -- Methods, Life on other planets -- Models, Biotic communities -- Models, Environmental issues, Science and technology, Zoology and wildlife conservation
Published
1988

23. Infrastructure, the economy and policy

Author

Huang, Jiashun, Farmer, Doyne, and Hall, Jim W.

Subjects
338.951
Abstract

The role of infrastructure in economic growth and development has been the subject of continued debate, yet no consensus has been achieved in the literature. This thesis examines the economic effect of infrastructure based on new evidence from China. We add to understanding of this complex phenomenon by focussing at micro levels, i.e., firm-level and household level with a focus on three critical infrastructure sectors: transport, renewable energy and information communication technologies. We employ a series of datasets on infrastructure, firm performance, and household economy from China in our examinations. Our first empirical study focuses on the economic effects of city’s ICT infrastructure on firm performance. We have found that the improvement of city’s ICT infrastructure positively improved firm’s profitability, marketing, and innovation. By taking advantage of an exogenous variation of city’s ICT using the telecommunication upgrade as a natural experiment, we establish the causal impact of city’s ICT infrastructure on firm profitability. We also identify the mechanisms in which ICTs impact firm performance, including the firm’s efficiency, firm’s labour, and firm cost. Our second empirical study focuses on the renewable energy sector and its influence on China’s rural household economy over the past two decades. We provide empirical evidence in this under-investigated area of research, and have found that renewable energy, including bioenergy, solar energy, and hydropower energy, indeed improved the rural household economy in China. In the third empirical study, we then focus on the impact of improved transport infrastructure connectivity on the litigation risks of listed firms in China. Based on a natural experiment on China’s highspeed rail system construction, we have found that the improvement of transport infrastructure connectivity reduced firm’s litigation risks. This study shows that the impact of improved transport connectivity on listed firms’ litigation risk stem from the reduction of information asymmetry, and also the increase of external regulations and monitoring. Overall, we have found evidence that transport infrastructure, renewable energy infrastructure and ICT infrastructure played a positive and critical role in the economic development from the perspectives of firm performance and household economy, and also provide in-depth analysis of the underlying mechanisms. The findings in this thesis offer evidence for policymakers that improvement of infrastructure contributes to the productivity, economic growth and social development, and reasonable deployment of infrastructure could pay off.

Published
2020

24. Input-output analysis and growth theory

Author

Savoie, Charles and Farmer, Doyne

Subjects
339.2
Abstract

This thesis studies a theory for the amplification of technological improvement by the production network structure of the economy. The theory is motivated by the idea that, to the extent that inputs and outputs of industries form a chain, improvements are passed down the chain and accumulate multiplicatively. Under a simple model for technological improvement it is possible to compute the overall improvement factor for the general case where the production network has a complicated structure containing cycles. We call this the trophic depth by analogy with ecology. This leads to testable predictions about GDP growth and its variance. We analyse data for 40 countries and 35 industries from 1995 to 2009 and demonstrate that trophic depths are strongly correlated with economic growth. A regression of GDP growth of countries against their trophic depths has a highly statistically significant R-squared equal to 0.38, and when other standard explanatory variables are added to the regression, the trophic depth remains a robust and statistically significant contributor. We perform some statistical analysis to understand the evolution of trophic depths at different stage of the economic development. We identify two growth paths. Along the first growth path, countries are catching up frontier economies while along the second growth path countries are falling behind. This approach allows us to make some forecasts about the evolution of trophic depths and of the wealth of countries. This provides a comprehensive framework to understand the acceleration and deceleration of economic growth. Then, we study another type of technological progress that corresponds to the adoption of new goods in the production chain. This mechanism is related to the dynamic of the production network and for this purpose we perform a link prediction analysis to determine some key factors for new adoptions. Finally, we analyse the relation between stock return comovement and institutional preferences across stocks of various size. A growing literature highlights the role of investors' common asset holdings on market dynamics. While previous studies focused on large stocks we also include small stocks in the sample in order to acknowledge the shift in institutional preferences towards small stocks over the last decades. Moreover, we add the input-output linkages between firms from different industries to our set of explanatory variables.

Published
2017

25. High-frequency dynamics of the microscopial structure in financial markets

Author

Vicente González, Francisco Javier, Farmer, Doyne, Tapia, Mikel, and Universidad Carlos III de Madrid. Departamento de Matemáticas

Subjects
Price dynamics, Non-Gaussian distributions, Matemáticas, Financial markets, Nonequilibrium physical systems
Abstract

In the first part of this thesis, I address the classical problem of asset price dynamics based on a new theoretical framework developed for nonequilibrium physical systems. This problem is mainly relevant for two reasons. First, because understanding the true distribution of returns is important for asset allocation, risk management, and option pricing. Second, because in spite of all the effort in determining the origin of non-Gaussian returns no conclusive result has been achieved yet. The most important result of this part is the demostration that the non-Gaussian shape and stable scaling of the returns distribution are due to slow, but significant, fluctuations in volatility. Futhermore, this result suggests that stock price fluctuations are universal, and that return distributions can be described by one functional form. In the second part, I present an empirical study about the execution of large orders in two stock exchanges: the London Stock Exchange, and the Spanish Stock Exchange. This type of orders can cause a tremendous impact because they are larger than the available liquidity in the order book at a time. For this reason, they are split to minimize transaction costs. Market price impact is the basic factor of these costs, so an accurate description of its functional form is necessary to any optimal execution. The most important result in this part is the empirical determination of this functional form in two markets and the finding of a common behavior in both markets that can be summarized into a concave temporary impact, roughly described by a square root function of the hidden order size, and a price reversion after the completion of the hidden order making permanent impact equal to roughly half of the temporary impact.

Published
2011

26. High-frequency dynamics of the microscopial structure in financial markets

Author

Vicente González, Javier, Farmer, Doyne, Tapia, Mikel, Universidad Carlos III de Madrid. Departamento de Matemáticas, and UC3M. Departamento de Matemáticas

Subjects
Price dynamics, Non-Gaussian distributions, Matemáticas, Financial markets, Nonequilibrium physical systems
Abstract

In the first part of this thesis, I address the classical problem of asset price dynamics based on a new theoretical framework developed for nonequilibrium physical systems. This problem is mainly relevant for two reasons. First, because understanding the true distribution of returns is important for asset allocation, risk management, and option pricing. Second, because in spite of all the effort in determining the origin of non-Gaussian returns no conclusive result has been achieved yet. The most important result of this part is the demostration that the non-Gaussian shape and stable scaling of the returns distribution are due to slow, but significant, fluctuations in volatility. Futhermore, this result suggests that stock price fluctuations are universal, and that return distributions can be described by one functional form. In the second part, I present an empirical study about the execution of large orders in two stock exchanges: the London Stock Exchange, and the Spanish Stock Exchange. This type of orders can cause a tremendous impact because they are larger than the available liquidity in the order book at a time. For this reason, they are split to minimize transaction costs. Market price impact is the basic factor of these costs, so an accurate description of its functional form is necessary to any optimal execution. The most important result in this part is the empirical determination of this functional form in two markets and the finding of a common behavior in both markets that can be summarized into a concave temporary impact, roughly described by a square root function of the hidden order size, and a price reversion after the completion of the hidden order making permanent impact equal to roughly half of the temporary impact.

Published
2011

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