Levels of Description: A Novel Approach to Dynamical Hierarchies

2005 ◽  
Vol 11 (4) ◽  
pp. 459-472 ◽  
Author(s):  
Simon McGregor ◽  
Chrisantha Fernando
Keyword(s):  
Information Theory ◽  
Dynamical Systems ◽  
Empirical Studies ◽  
State Dependence ◽  
Partial Ordering ◽  
Living Systems ◽  
Novel Approach ◽  
Dependence Criterion

We present a novel formal interpretation of dynamical hierarchies based on information theory, in which each level is a near-state-determined system, and levels are related to one another in a partial ordering. This reformulation moves away from previous definitions, which have considered unique hierarchies of structures or objects arranged in aggregates. Instead, we consider hierarchies of dynamical systems: these are more suited to describing living systems, which are not mere aggregates, but organizations. Transformations from lower to higher levels in a hierarchy are redescriptions that lose information. There are two criteria for partial ordering. One is a state-dependence criterion enforcing predictability within a level. The second is a distinctness criterion enforcing the idea that the higher-level description must do more than just throw information away. We hope this will be a useful tool for empirical studies of both computational and physical dynamical hierarchies.

A novel approach for the stability problem in non-linear dynamical systems

2003 ◽  
Vol 155 (1) ◽  
pp. 21-30 ◽  
Author(s):  
Tarcı́sio M. Rocha Filho ◽  
Iram M. Gléria ◽  
Annibal Figueiredo
Keyword(s):  
Dynamical Systems ◽  
Stability Problem ◽  
Linear Dynamical Systems ◽  
Novel Approach ◽  
Non Linear ◽  
The Stability

scholarly journals On Crashing the Barrier of Meaning in Artificial Intelligence

AI Magazine ◽  
2020 ◽  
Vol 41 (2) ◽  
pp. 86-92 ◽  
Author(s):  
Melanie Mitchell
Keyword(s):  
Artificial Intelligence ◽  
Information Theory ◽  
Animal Behavior ◽  
Developmental Psychology ◽  
Living Systems ◽  
Santa Fe ◽  
Dawn Song ◽  
Artificial Intelligence Systems

In 1986, the mathematician and philosopher Gian-Carlo Rota wrote, “I wonder whether or when artificial intelligence will ever crash the barrier of meaning” (Rota 1986). Here, the phrase “barrier of meaning” refers to a belief about humans versus machines: Humans are able to actually understand the situations they encounter, whereas even the most advanced of today’s artificial intelligence systems do not yet have a humanlike understanding of the concepts that we are trying to teach them. This lack of understanding may underlie current limitations on the generality and reliability of modern artificial intelligence systems. In October 2018, the Santa Fe Institute held a three-day workshop, organized by Barbara Grosz, Dawn Song, and myself, called Artificial Intelligence and the Barrier of Meaning. Thirty participants from a diverse set of disciplines — artificial intelligence, robotics, cognitive and developmental psychology, animal behavior, information theory, and philosophy, among others — met to discuss questions related to the notion of understanding in living systems and the prospect for such understanding in machines. In the hope that the results of the workshop will be useful to the broader community, this article summarizes the main themes of discussion and highlights some of the ideas developed at the workshop.

scholarly journals On the Scales of Selves: Information, Life, and Buddhist Philosophy

2021 ◽  
Author(s):  
Carlos Gershenson
Keyword(s):  
Information Theory ◽  
Buddhist Philosophy ◽  
Living Systems

When we attempt to define life, we tend to refer to individuals, those that are alive. But these individuals might be cells, organisms, colonies... ecosystems? We can describe living systems at different scales. Which ones might be the best ones to describe different selves? I explore this question using concepts from information theory, ALife, and Buddhist philosophy. After brief introductions, I review the implications of changing the scale of observation, and how this affects our understanding of selves at different structural, temporal, and informational scales. The conclusion is that there is no single ``best'' scale for a self, as this will depend on the scale at which decisions must be made. Different decisions, different scales.

scholarly journals Some Problems of Feedback Control Strategies and It’s Treatment

2017 ◽  
Vol 9 (1) ◽  
pp. 39 ◽  
Author(s):  
Maysoon M. Aziz ◽  
Saad Fawzi AL-Azzawi
Keyword(s):  
Dynamical Systems ◽  
Feedback Control ◽  
Numerical Simulations ◽  
Positive Feedback ◽  
Control Strategies ◽  
Novel Approach

This paper extends and improves the feedback control strategies. In detailed, the ordinary feedback, dislocated feedback, speed feedback and enhancing feedback control for a several dynamical systems are discussed here. It is noticed that there some problems by these strategies. For this reason, this Letter proposes a novel approach for treating these problems. The results obtained in this paper show that the strategies with positive feedback coefficients can be controlled in two cases and failed in another two cases. Theoretical and numerical simulations are given to illustrate and verify the results.

scholarly journals Spatio-temporal patterns with hyperchaotic dynamics in diffusively coupled biochemical oscillators

1997 ◽  
Vol 1 (2) ◽  
pp. 161-167 ◽  
Author(s):  
Gerold Baier ◽  
Sven Sahle
Keyword(s):  
Dynamical Systems ◽  
Finite Number ◽  
Temporal Patterns ◽  
Autocatalytic Reaction ◽  
Living Systems ◽  
First Order ◽  
Autocatalytic Reactions ◽  
Complex Patterns ◽  
Spatio Temporal

We present three examples how complex spatio-temporal patterns can be linked to hyperchaotic attractors in dynamical systems consisting of nonlinear biochemical oscillators coupled linearly with diffusion terms. The systems involved are: (a) a two-variable oscillator with two consecutive autocatalytic reactions derived from the Lotka–Volterra scheme; (b) a minimal two-variable oscillator with one first-order autocatalytic reaction; (c) a three-variable oscillator with first-order feedback lacking autocatalysis. The dynamics of a finite number of coupled biochemical oscillators may account for complex patterns in compartmentalized living systems like cells or tissue, and may be tested experimentally in coupled microreactors.

Clustering Approaches for Top-k Recommender Systems

2019 ◽  
Vol 28 (05) ◽  
pp. 1950019 ◽  
Author(s):  
Nicolás Torres ◽  
Marcelo Mendoza
Keyword(s):  
Recommender Systems ◽  
Recommender System ◽  
Large Scale ◽  
Empirical Studies ◽  
Cluster Structure ◽  
Parallel Architecture ◽  
Evaluation Framework ◽  
Training Data ◽  
Cluster Solution ◽  
Novel Approach

Clustering-based recommender systems bound the seek of similar users within small user clusters providing fast recommendations in large-scale datasets. Then groups can naturally be distributed into different data partitions scaling up in the number of users the recommender system can handle. Unfortunately, while the number of users and items included in a cluster solution increases, the performance in terms of precision of a clustering-based recommender system decreases. We present a novel approach that introduces a cluster-based distance function used for neighborhood computation. In our approach, clusters generated from the training data provide the basis for neighborhood selection. Then, to expand the search of relevant users, we use a novel measure that can exploit the global cluster structure to infer cluster-outside user’s distances. Empirical studies on five widely known benchmark datasets show that our proposal is very competitive in terms of precision, recall, and NDCG. However, the strongest point of our method relies on scalability, reaching speedups of 20× in a sequential computing evaluation framework and up to 100× in a parallel architecture. These results show that an efficient implementation of our cluster-based CF method can handle very large datasets providing also good results in terms of precision, avoiding the high computational costs involved in the application of more sophisticated techniques.

scholarly journals Understanding and Predicting Nonlinear Turbulent Dynamical Systems with Information Theory

Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 248
Author(s):  
Nan Chen ◽  
Xiao Hou ◽  
Qin Li ◽  
Yingda Li
Keyword(s):  
Information Theory ◽  
Dynamical Systems ◽  
Information Criterion ◽  
Gaussian Mixture ◽  
Model Error ◽  
High Dimensions ◽  
New Approach ◽  
Fluctuation Dissipation ◽  
Spectrum Density ◽  
Non Gaussian

Complex nonlinear turbulent dynamical systems are ubiquitous in many areas. Quantifying the model error and model uncertainty plays an important role in understanding and predicting complex dynamical systems. In the first part of this article, a simple information criterion is developed to assess the model error in imperfect models. This effective information criterion takes into account the information in both the equilibrium statistics and the temporal autocorrelation function, where the latter is written in the form of the spectrum density that permits the quantification via information theory. This information criterion facilitates the study of model reduction, stochastic parameterizations, and intermittent events. In the second part of this article, a new efficient method is developed to improve the computation of the linear response via the Fluctuation Dissipation Theorem (FDT). This new approach makes use of a Gaussian Mixture (GM) to describe the unperturbed probability density function in high dimensions and avoids utilizing Gaussian approximations in computing the statistical response, as is widely used in the quasi-Gaussian (qG) FDT. Testing examples show that this GM FDT outperforms qG FDT in various strong non-Gaussian regimes.

scholarly journals Money: An Integrated Review and Synthesis From a Psychological Perspective

2020 ◽  
Vol 24 (2) ◽  
pp. 172-190 ◽  
Author(s):  
Xijing Wang ◽  
Zhansheng Chen ◽  
Eva G. Krumhuber
Keyword(s):  
Empirical Studies ◽  
Goal Pursuit ◽  
Self Esteem ◽  
Psychological Perspective ◽  
Review Of The Literature ◽  
Social Distinction ◽  
Novel Approach ◽  
Broad Concept ◽  
Underlying Mechanisms ◽  
Future Work

Many empirical studies have demonstrated the psychological effects of various aspects of money, including the aspiration for money, mere thoughts about money, possession of money, and placement of people in economic contexts. Although multiple aspects of money and varied methodologies have been focused on and implemented, the underlying mechanisms of the empirical findings from these seemingly isolated areas significantly overlap. In this article, we operationalize money as a broad concept and take a novel approach by providing an integrated review of the literature and identifying five major streams of mechanisms: (a) self-focused behavior; (b) inhibited other-oriented behavior; (c) favoring of a self–other distinction; (d) money’s relationship with self-esteem and self-efficacy; and (e) goal pursuit, objectification, outcome maximization, and unethicality. Moreover, we propose a unified psychological perspective for the future—money as an embodiment of social distinction—which could potentially account for past findings and generate future work.

Macroreticulate buffers: a novel approach to pH control in living systems

1991 ◽  
Vol 17 (2) ◽  
pp. 169-176 ◽  
Author(s):  
Pier Giorgio Righetti ◽  
Marcella Chiari ◽  
Laura Crippa
Keyword(s):  
Ph Control ◽  
Living Systems ◽  
Novel Approach
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