The article discusses the use of algorithmic models in finance (algo or high frequency trading). Algo trading is widespread but also somewhat controversial in modern financial markets. It is a form of automated trading technology, which critics claim can, among other things, lead to market manipulation. Drawing on three cases, this article shows that manipulation also can happen in the reverse way, meaning that human traders attempt to make algorithms ‘make mistakes’ by ‘misleading’ them. These attempts to manipulate are (...) very simple and immediately transparent to humans. Nevertheless, financial regulators increasingly penalize such attempts to manipulate algos. The article explains this as an institutionalization of algo trading, a trading practice which is vulnerable enough to need regulatory protection. (shrink)

Aesthetic theory distinguishes different approaches to understanding the sensory and logical. The author agrees with I. Kant’s theory that sensory perception is subjective and the imagination is given the opportunity to invent fictional characters that do not exist in real life. Digital technologies make it possible to revive and introduce such characters into an artistic performance. This process becomes possible with the help of computer algorithms that are used to create art practices. There are many contradictory publications where (...) there is no understanding of the technological process of the task at hand, for example, that it is possible to write a program that will “teach machine aesthetics” using pictures. Therefore, the author turns to three technological solutions (virtual reality, augmented reality and artificial intelligence or neural networks) and examines, using the example of existing programs and applications, how the process of interacting computer algorithms of artistic creativity with the imagination and skill of stage work directors (play, opera, choreography). The author solves this issue within the framework of algorithmic aesthetics, which considers the process of communication, but unlike media theory, considers the process of information exchange in binary code. The algorithms by which the written programs operate do not create a “code spirit”, but allow the creation of tools for artistic creativity and the development of the skills of talented people. (shrink)

Adaptive dynamic programming, which belongs to the field of computational intelligence, is a powerful tool to address optimal control problems. To overcome the bottleneck of solving Hamilton–Jacobi–Bellman equations, several state-of-the-art ADP approaches are reviewed in this paper. First, two model-based offline iterative ADP methods including policy iteration and value iteration are given, and their respective advantages and shortcomings are discussed in detail. Second, the multistep heuristic dynamic programming method is introduced, which avoids the requirement of initial admissible control and achieves (...) fast convergence. This method successfully utilizes the advantages of PI and VI and overcomes their drawbacks at the same time. Finally, the discrete-time optimal control strategy is tested on a power system. (shrink)

The computational program for theoretical neuroscience initiated by Marr and Poggio (1977) calls for a study of biological information processing on several distinct levels of abstraction. At each of these levels — computational (defining the problems and considering possible solutions), algorithmic (specifying the sequence of operations leading to a solution) and implementational — significant progress has been made in the understanding of cognition. In the past three decades, computational principles have been discovered that are common to a wide range of (...) functions in perception (vision, hearing, olfaction) and action (motor control). More recently, these principles have been applied to the analysis of cognitive tasks that require dealing with structured information, such as visual scene understanding and analogical reasoning. Insofar as language relies on cognition-general principles and mechanisms, it should be possible to capitalize on the recent advances in the computational study of cognition by extending its methods to linguistics. (shrink)

Diverse leadership in information and communication technology can be defined as an approach to empower digital innovation. Digital innovation is a key driver of digital and business transformation. This process demands human transformation to complement business transformation in order to achieve long term sustainability. Changing the culture, fostering an inclusive mindset and guaranteeing diversity are challenging yet foundational elements in building a legacy and require inclusive digital ethics leadership. Our society needs to undergo disruptive and transformative changes in order to (...) adapt to exponential technological advances in the educational, professional, cultural and governance fields. The digital era holds great potential for increased inclusion, reduction or even closure of the „Gender Leadership Gap “in all industries, especially in the Construction and IT industry, Research and Development sectors, as well as in Academia where women are still underrepresented. This article analyzes how diverse leadership in ICT is a moral imperative for our society, emphasizes the need to recalibrate and reshape our approach and highlights the benefits of leveraging women’s potential in the social, digital and business transformation arenas. This article aims to fill an ‘ethical vacuum’ brought to light by the emerging technologies` revolution, focuses on both ethical and data governance aspects in digital innovation and offers approaches to answer how diverse leadership can contribute towards avoiding gender bias, optimizing inclusion and further improve crucial digital ethics aspects in data-driven technologies - such as algorithmic bias, fairness, transparency in AI. (shrink)

Two analyzes of Spark engine performance strategies to implement the Spark technique in a matrix distributed computational algorithm, the multiplication of a sparse multiplication operational test model. The dimensions of the two input sparse matrices have been fixed to 30,000 × 30,000, and the density of the input matrix have been changed. The experimental results show that when the density reaches about 0.3, the original dense matrix multiplication performance can outperform the sparse-sparse matrix multiplication, which is basically consistent with the (...) relationship between the sparse matrix multiplication implementation in the single-machine sparse matrix test and the computational performance of the local native library. When the density of the fixed sparse matrix is 0.01, the distributed density-sparse matrix multiplication outperforms the same sparsity but uses the density matrix storage, and the acceleration ratio increases from 1.88× to 5.71× with the increase in dimension. The overall performance of distributed operations is improved. (shrink)

Evapotranspiration represents the water requirement of plants during their growing season, and its accurate measurement at the farm is essential for agricultural water planners and managers. Field measurements of evapotranspiration have always been associated with many difficulties that have led researchers to seek a way to remotely measure this component in horticultural and agricultural areas. This study aims to investigate an indirect approach for daily rice crop evapotranspiration measurement by machine learning techniques and the least available climatic variables. For this (...) purpose, daily meteorological variables were obtained from three ground meteorological stations in rice cultivation regions of northern Iran during 2003–2016. The ETc rates were calculated by seven meteorological variables, the FAO-56 Penman-Monteith equation, and the regional calibrated rice crop coefficient and considered as the reference data. The MLs, including Multilayer Perceptron, Radial Basis Function, Generalized Regression Neural Network, and Group Method of Data Handling, were utilized for ETc modeling. Different input combinations were applied, based on the use of minimum effective variables as input. Results showed that the models showed the most accurate performances in the input combination of four climatic variables: sunshine duration, maximum temperature, relative humidity, and wind speed. Investigating the accuracy of models in rice growth phases showed that the least estimation error belonged to the initial growing stage, which increased during the mid-season and late-season growing stages. A comparison of the models showed that the GMDH model performed better against the other competitors. For this model, both the Nash-Sutcliffe coefficient and R2 were greater than 0.98, and the Root Mean Square Error ranged between 0.214 and 0.234 mm per day in all stations. The current approach showed promising results in rice evapotranspiration modeling by only four common meteorological variables and can be reliably applied for indirect measurement of this variable over the rice farms. The studied approach will have research value for rice and other crops in similar/different climatic conditions. (shrink)

Machine awareness is a disputed research topic, in some circles considered a crucial step in realising Artificial General Intelligence. Understanding what that is, under which conditions such feature could arise and how it can be controlled is still a matter of speculation. A more concrete object of theoretical analysis is algorithmic iteration for computational intelligence, intended as the theoretical and practical ability of algorithms to design other algorithms for actions aimed at solving well-specified tasks. We know this ability (...) is already shown by current AIs, and understanding its limits is an essential step in qualifying claims about machine awareness and Super-AI. We propose a formal translation of algorithmic iteration in a fragment of modal logic, formulate principles of transparency and faithfulness across human and machine intelligence, and consider the relevance to theoretical research on -AI as well as the practical import of our results. (shrink)

Every scientist chooses a preferred level of analysis and this choice shapes the research program, even determining what counts as evidence. This contribution revisits Marr's three levels of analysis and evaluates the prospect of making progress at each individual level. After reviewing limitations of theorizing within a level, two strategies for integration across levels are considered. One is top–down in that it attempts to build a bridge from the computational to algorithmic level. Limitations of this approach include insufficient theoretical constraint (...) at the computation level to provide a foundation for integration, and that people are suboptimal for reasons other than capacity limitations. Instead, an inside-out approach is forwarded in which all three levels of analysis are integrated via the algorithmic level. This approach maximally leverages mutual data constraints at all levels. For example, algorithmic models can be used to interpret brain imaging data, and brain imaging data can be used to select among competing models. Examples of this approach to integration are provided. This merging of levels raises questions about the relevance of Marr's tripartite view. (shrink)

In this paper we present some algorithms for computing minimal conflicts. First of all we discuss the relationship between minimal conflicts and minimally inconsistent subsets. Then we introduce an algorithm for computing all minimally inconsistent subsets, which is applied to generating all minimal conflicts. Furthermore, an algorithm for computing all minimal conflicts using structured description is introduced, and its correctness is proved; its time complexity is also shown. The algorithm using structured description terminates in polynomial time for some special (...) system, such as the tree–structured systems. The algorithms are also complared with related works. (shrink)

The ideas of quantum simulation and advances in quantum algorithms to solve quantum chemistry problems have been discussed. Theoretical proposals and experimental investigations both have been studied to gauge the extent to which quantum computation has been applied to solve quantum chemical problems till date. The distinctive features and limitations of the application of quantum simulation on chemical systems and current approaches to define and improve upon standard quantum algorithms have been studied in detail. The possibility and consequences (...) of designing an efficient quantum computer that can address chemical problems have been assessed. The experimental realization of quantum supremacy defies the conventional belief of chemists, that millions of qubits would be required to solve fundamental chemistry problems. It is predicted that quantum simulation of quantum chemistry problems will radically revolutionize this field. (shrink)

In this paper, we propose a framework capable of dealing with anaphora and ellipsis which is both general and algorithmic. This generality is ensured by the compination of two general ideas. First, we use a dynamic semantics which reperent effects using a monad structure. Second we treat scopes flexibly, extending them as needed. We additionally implement this framework as an algorithm which translates abstract syntax to logical formulas. We argue that this framework can provide a unified account of a large (...) number of anaphoric phenomena. Specifically, we show its effectiveness in dealing with pronominal and VP-anaphora, strict and lazy pronouns, lazy identity, bound variable anaphora, e-type pronouns, and cataphora. This means that in particular we can handle complex cases like Bach–Peters sentences, which require an account dealing simultaneously with several phenomena. We use Haskell as a meta-language to present the theory, which also consitutes an implementation of all the phenomena discussed in the paper. To demonstrate coverage, we propose a test suite that can be used to evaluate computational approaches to anaphora. (shrink)

In our contemporary moment, when machine learning algorithms are reshaping many aspects of society, the work of N. Katherine Hayles stands as a powerful corpus for understanding what is at stake in a new regime of computation. A renowned literary theorist whose work bridges the humanities and sciences among her many works, Hayles has detailed ways to think about embodiment in an age of virtuality ( How We Became Posthuman, 1999), how code as performative practice is located ( My (...) Mother Was a Computer, 2005), and the reciprocal relations among human bodies and technics ( How We Think, 2012). This special issue follows the 2017 publication of her book Unthought: The Power of the Cognitive Nonconscious, in which Hayles traces the nonconscious cognition of biological life-forms and computational media. The articles in the special issue respond in different ways to Hayles’ oeuvre, mapping the specific contours of computational regimes and developing some of the ‘inflection points’ she advocates in the deep engagement with technical systems. (shrink)

In this paper, building on these previous works, we propose to go deeper into the understanding of crowd behavior by proposing an approach which integrates ontologi- cal models of crowd behavior and dedicated computer vision algorithms, with the aim of recognizing some targeted complex events happening in the playground from the observation of the spectator crowd behavior. In order to do that, we first propose an ontology encoding available knowledge on spectator crowd behavior, built as a spe- cialization (...) of the DOLCE foundational ontology, which allows the representation of categories belonging both to the physical and to the social realms. We then propose a simplified and tractable version of such ontology in a new temporal extension of a description logic, which is used for temporally coupling events happening on the play- ground and spectator crowd behavior. At last, computer vision algorithms provide the input information concerning what is observed on the stands and ontological reasoning delivers the output necessary to perform complex event recognition. (shrink)

Introduction -- Algorithms, programs, procedures, and abstract automata -- Functioning of algorithms and automata, computation, and operations with algorithms and automata -- Basic postulates and axioms for algorithms -- Power of algorithms and classes of algorithms: comparison and evaluation -- Computing, accepting, and deciding modes of algorithms and programs -- Problems that people solve and related properties of algorithms -- Boundaries for algorithms and computation -- Software and hardware verification and testing (...) -- Conclusion. (shrink)

The idea that human thought requires the execution of mental algorithms provides a foundation for research programs in cognitive science, which are largely based upon the computational conception of language and mentality. Consideration is given to recent work by Penrose, Searle, and Cleland, who supply various grounds for disputing computationalism. These grounds in turn qualify as reasons for preferring a non-computational, semiotic approach, which can account for them as predictable manifestations of a more adquate conception. Thinking does not ordinarily (...) require the execution of mental algorithms, which appears to be at best no more than one rather special kind of thinking. (shrink)

Abstract This chapter is interested in the epistemology of algorithms. As I intend to approach the topic, this is an issue about epistemic justification. Current approaches to justification emphasize the transparency of algorithms, which entails elucidating their internal mechanisms –such as functions and variables– and demonstrating how (or that) these produce outputs. Thus, the mode of justification through transparency is contingent on what can be shown about the algorithm and, in this sense, is internal to the algorithm. In (...) contrast, I advocate for an externalist epistemology of algorithms that I term computational reliabilism (CR). While I have previously introduced and examined CR in the field of computer simulations ([42, 53, 4]), this chapter extends this reliabilist epistemology to encompass a broader spectrum of algorithms utilized in various scientific disciplines, with a particular emphasis on machine learning applications. At its core, CR posits that an algorithm’s output is justified if it is produced by a reliable algorithm. A reliable algorithm is one that has been specified, coded, used, and maintained utilizing reliability indicators. These reliability indicators stem from formal methods, algorithmic metrics, expert competencies, cultures of research, and other scientific endeavors. The primary aim of this chapter is to delineate the foundations of CR, explicate its operational mechanisms, and outline its potential as an externalist epistemology of algorithms. (shrink)

:Brain–computer interfaces are driven essentially by algorithms; however, the ethical role of such algorithms has so far been neglected in the ethical assessment of BCIs. The goal of this article is therefore twofold: First, it aims to offer insights into whether the problems related to the ethics of BCIs can be better grasped with the help of already existing work on the ethics of algorithms. As a second goal, the article explores what kinds of solutions are (...) available in that body of scholarship, and how these solutions relate to some of the ethical questions around BCIs. In short, the article asks what lessons can be learned about the ethics of BCIs from looking at the ethics of algorithms. To achieve these goals, the article proceeds as follows. First, a brief introduction into the algorithmic background of BCIs is given. Second, the debate about epistemic concerns and the ethics of algorithms is sketched. Finally, this debate is transferred to the ethics of BCIs. (shrink)

Let G = V G, E G be a molecular graph, where V G and E G are the sets of vertices and edges. A topological index of a molecular graph is a numerical quantity which helps to predict the chemical/physical properties of the molecules. The Wiener, Wiener polarity, and the terminal Wiener indices are the distance-based topological indices. In this paper, we described a linear time algorithm that computes the Wiener index for acyclic graphs and extended this algorithm for (...) unicyclic graphs. The same algorithms are modified to compute the terminal Wiener index and the Wiener polarity index. All these algorithms compute the indices in time O n. (shrink)

Marr's levels of analysis—computational, algorithmic, and implementation—have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea is to push the (...) notion of rationality, often used in defining computational-level models, deeper toward the algorithmic level. We offer a simple recipe for reverse-engineering the mind's cognitive strategies by deriving optimal algorithms for a series of increasingly more realistic abstract computational architectures, which we call “resource-rational analysis.”. (shrink)

The fuzzy clustering algorithm has been widely used in the research area and production and life. However, the conventional fuzzy algorithms have a disadvantage of high computational complexity. This article proposes an improved fuzzy C-means algorithm based on K-means and principle of granularity. This algorithm is aiming at solving the problems of optimal number of clusters and sensitivity to the data initialization in the conventional FCM methods. The initialization stage of the K-medoid cluster, which is different from others, has (...) a strong representation and is capable of detecting data with different sizes. Meanwhile, through the combination of the granular computing and FCM, the optimal number of clusters is obtained by choosing accurate validity functions. Finally, the detailed clustering process of the proposed algorithm is presented, and its performance is validated by simulation tests. The test results show that the proposed improved FCM algorithm has enhanced clustering performance in the computational complexity, running time, cluster effectiveness compared with the existing FCM algorithms. (shrink)

In this paper, building on these previous works, we propose to go deeper into the understanding of crowd behavior by proposing an approach which integrates ontologi- cal models of crowd behavior and dedicated computer vision algorithms, with the aim of recognizing some targeted complex events happening in the playground from the observation of the spectator crowd behavior. In order to do that, we first propose an ontology encoding available knowledge on spectator crowd behavior, built as a spe- cialization (...) of the DOLCE foundational ontology, which allows the representation of categories belonging both to the physical and to the social realms. We then propose a simplified and tractable version of such ontology in a new temporal extension of a description logic, which is used for temporally coupling events happening on the play- ground and spectator crowd behavior. At last, computer vision algorithms provide the input information concerning what is observed on the stands and ontological reasoning delivers the output necessary to perform complex event recognition. (shrink)

The computational approach to psychiatric disorders, including delusions, promises explanation and treatment. Here, we argue that an information processing approach might be misleading to understand psychopathology and requires further refinement. We explore the claim of computational psychiatry being a bridge between phenomenology and physiology while focussing on the ontological commitments and corresponding methodology computational psychiatry is based on. Interconnecting ontological claims and methodological practices, the paper illustrates the structure of theory-building and testing in computational psychiatry.First, we will explain the ontological (...) commitments computational psychiatry is grounded in, theBayesian Brain hypothesis(BBH) of unconscious inference, paired with normative deontic approaches applied to gauge psychopathology. We then turn to the steps taken in empirical paradigms, from definitions, which are used as starting points, to the operationalisation and isolation of cognitive processes and hypothesis testing based on algorithmic models, to consecutive interpretations regarding the aetiology of psychiatric disorders. We outline how experimental paradigms in computational psychiatry are specifically designed to confirm aberrations in assumed inferential processes, which are thought of as being the underlyingcore invariant features.We will illustrate a gap between the ontological commitments of computational psychiatry and the operationalisation and testing of the cognition assumed to be relevant for psychopathology. This conceptual gap is of utmost importance when designing computational paradigms and may impede a crisp understanding of the approach. Lastly, in evaluating the conceptual gap, it becomes apparent that the information processing formalism used in computational psychiatry is still grounded in rational cognitive psychology. (shrink)

In recent years, with the development of construction industry, more scientific, systematic, fast, and intelligent calculation methods are needed to coordinate urban development and fierce market competition, and mathematical algorithm library plays an important role in artificial intelligence. Therefore, the author uses computer mathematical algorithm and extension theory to study and analyze the residential building design and intelligent data mining. It is found that the research of the computer-aided expression method of extension building planning is mainly the expression (...) of the input and output system of extension building planning. It includes knowledge representation, system outline design, system flow, and interface expression based on the mathematical database. (shrink)

The existing computer technology is used to conduct an in-depth study and analysis of drilling waste treatment, and the results are analyzed by computer simulation optimization algorithms. Based on the system theory, we define the research system, combine the unique characteristics of the technological innovation mechanism of drilling waste treatment, and use the internal and external factors affecting the technological innovation dynamics of drilling waste treatment, such as drilling waste treatment capacity, from the current actual situation. On (...) this basis, factor analysis is used to analyze the factors affecting technological innovation dynamics from both internal and external aspects of the system, establish a system model of technological innovation dynamics of drilling waste disposal, and give the initial values of the simulation model. This will reduce the pollution of the environment and enhance the competitiveness of enterprises. Drilling waste treatment technology is getting increased attention, but at this stage, there is no suitable technology innovation mechanism for drilling waste treatment. Through the simulation trend chart obtained by sensitivity analysis, the key factors in the system are found, and the innovation power mechanism of drilling waste treatment technology is constructed, which provides a basis for the formulation of enterprise technological innovation strategies and the development of technological innovation activities. Research on the dynamic mechanism of drilling waste treatment technology innovation explores a waste treatment mechanism suitable for the drilling industry, so as to promote the steady development of the drilling industry and at the same time provide theoretical support for the treatment of drilling engineering waste. (shrink)

Hi everybody! It's a great pleasure for me to be back here at the new, improved Santa Fe Institute in this spectacular location. I guess this is my fourth visit and it's always very stimulating, so I'm always very happy to visit you guys. I'd like to tell you what I've been up to lately. First of all, let me say what algorithmic information theory is good for, before telling you about the new version of it I've got.

People recognize faces of their own race more accurately than faces of other races. The “contact” hypothesis suggests that this “other‐race effect” occurs as a result of the greater experience we have with own‐ versus other‐race faces. The computational mechanisms that may underlie different versions of the contact hypothesis were explored in this study. We replicated the other‐race effect with human participants and evaluated four classes of computational face recognition algorithms for the presence of an other‐race effect. Consistent with (...) the predictions of a developmental contact hypothesis, “experience‐based models” demonstrated an other‐race effect only when the representational system was developed through experience that warped the perceptual space in a way that was sensitive to the overall structure of the model's experience with faces of different races. When the model's representation relied on a feature set optimized to encode the information in the learned faces, experience‐based algorithms recognized minority‐race faces more accurately than majority‐race faces. The results suggest a developmental learning process that warps the perceptual space to enhance the encoding of distinctions relevant for own‐race faces. This feature space limits the quality of face representations for other‐race faces. (shrink)

This article analyzes current attitudes toward artificial intelligence (AI) and quantum computing and argues that they represent a modern‐day form of magical thinking. It proposes that AI and quantum computing are thus excellent examples of the ways that traditional distinctions between religion, science, and magic fail to account for the vibrancy and energy that surround modern technologies.

1. Argumentation, by considering arguments and their interactions, is a way of reasoning that has proven successful in many contexts, for instance, in multi-agent applications (Carrera & Iglesias,...

The topology optimization of computer communication network is studied based on improved genetic algorithm, a network optimization design model based on the establishment of network reliability maximization under given cost constraints, and the corresponding improved GA is proposed. In this method, the corresponding computer communication network cost model and computer communication network reliability model are established through a specific project, and the genetic intelligence algorithm is used to solve the cost model and computer communication network reliability (...) model, respectively. It has been proved that GA can solve the complex problems of computer working environment better, which is 80% higher than the general algorithm, and can select the optimal scheme pertinently. (shrink)

Review of The Computational Theory of Mind by Matteo Colombo and Gualtiero Piccinini. Cambridge, 2023, iv + 75 pp, $64.99 HB.