The ultimate goal of research in cognitive architectures is to model the human mind, eventually enabling the recreation of human-level artificial intelligence. However current wave of research in cognitive architectures is centered only on the study of human mind modeling occupied with the human behavior and the underlying cognitive mechanisms necessary for implementation of this behavior. In doing so, human mind research totally derails its own ability to study other operating mechanisms of biological brains, such as how the brain processes information, evaluates its semantics, makes decisions and interacts with the surrounding world. The prime intention of this short comment on the current trends in the human brain research is to draw people's attention to the harmful consequences of some of such trends.
The article discusses the principles of operation of the minimal consciousness of a cognitive cyber-physical system and an example of the implementation of this system in the form of an autonomous trolley with three supports. The trolley is equipped with minimal consciousness and will navigate locally and follow a predetermined route. The minimal consciousness will control the actions of the trolley based on the analysis of data of its own position, speed, deviation from the given route, etc. It is proposed to implement two variants of minimal consciousness: 1) in the form of stream production system that may be presented as a composition of finite-state machines with feedback and finite-state automates; 2) in the form of a temporal-casual neural network. Experiments to compare the two implementation variants will be aimed at further improvement of robotic platforms and an expansion of their versatility. The design of cyber-physical systems equipped with machine consciousness is the key to obtaining reliable systems, as it potentially increases their behavioral flexibility in new or changing environments, their resilience to failures in the operation or interaction of their components.
In this work we address the use of visualization tools for developing intelligent agents built with Cognitive Architectures (CAs). Unfortunately, there are just a few discussions about this issue in the CAs literature. We start by bringing a summary on how this topic is currently being addressed within the community and further introduce our efforts in building visualization tools for both debugging and aiding the understanding of the inner mechanisms of a CA. For this, we propose the MindViewer, a visualization tool for monitoring and debugging CAs constructed with CST, the Cognitive Systems Toolkit. MindViewer encompasses a variety of charts that are used to monitor the inner details of the agents’ mind. Its Web version allows inspect even complex data structures and customize their generated graphics. We exemplify their capabilities through a experimental application based on a robot simulation inspired in Iowa Gambling Task.
We describe a cognitive architecture intended to solve a wide range of problems based on the five identified principles of brain activity, with their implementation in three subsystems: logical-probabilistic inference, probabilistic formal concepts, and functional systems theory. Building an architecture involves the implementation of a task-driven approach that allows defining the target functions of applied applications as tasks formulated in terms of the operating environment corresponding to the task, expressed in the applied ontology. We provide a basic ontology for a number of practical applications as well as for the subject domain ontologies based upon it, describe the proposed architecture, and give possible examples of the execution of these applications in this architecture.
This article discusses a mechanism with six kinematic chains (legs) and 18 degrees of freedom – a hexabot robot. The equations of kinematics and dynamics of a separate leg of a robot with three degrees of freedom are written out. The issue of optimizing the movement of the robot based on the study of dynamic equations is considered. The derivation of the dynamics equation of the leg, compiled on the basis of the Lagrange- equation of the 2nd kind, is presented. It is noted that walking robots have an indisputable advantage over other types of movement on the surface in such tasks as moving along sandy and swampy surfaces, moving off-road and in difficult terrain, moving under water. The use of mechanisms (robots) on a wheeled or caterpillar basis in such conditions seems impossible or ineffective.
This article analyzes the role of the cognitive mechanism of temporal transspective in the organization of natural cognitive architectures in human speech communication. Psychological situations and factors of actualization of the temporal aspect of events by a person are established. These include four types of situations and motivation: the need to accelerate, slow down actions / events, prolong, and stop impressions / events. Using psychological analysis, the facts of the speech behavior of children, adolescents and adults are analyzed, the similarity and difference in the implementation of the mechanism of temporal transspective at different ages are shown. The mechanism of temporal transspective is characterized as an early cognitive mechanism. The fundamental role of this mechanism in the hierarchy and dynamics of distributed cognitive architectures from the moment of conception of speech to the moment of achievement of communicative goals is established. The invariant content of the temporal transspective mechanism is established, taking into account the level of cognitive architectures that ensure the process of speech communication. This information is relevant for the development of age-oriented artificial intelligence technologies and social robots.
This paper presents a formalization of the "following the leader" task and an implementation of the environment emulator based on that formalization for training a neural network model that solves this task. The emulator is based on the path planning algorithm that creates the leader route used in the training process of the neural network model. The paper presents a comparative evaluation of the speed of a number of path planning algorithms with the choice of the best one. In the created emulator, it is possible to set up an environment with a different number of obstacles, routes of different lengths and complexity, as well as set up the desired behavior of the agent following the leader. Due to the speed of the developed emulator, it allows training leader-following models based on reinforcement learning technology, the tuning process of which requires a large number of training iterations in various environments.
In this paper, an adaptive network model is presented of neurodegeneration processes over time. Mechanisms involved in these processes were used in the model which was used for computational analysis. This analysis provided insights into the interaction between the role of risk and protective factors with respect to lipid and alpha-synuclein homeostasis dysfunction. Different scenarios of disease progression have been addressed which can potentially be used to regard particular cases of PD.
Several maturity models for organizations, their subsystems and processes, for example, information security (IS) incident management are known. Continuing our earlier analysis of the most common maturity models (MMs), models and approaches to assessing the maturity level (ML) of organization's IS management (ISM) maturity, namely The Bank of Russia's ISM MM, ISMS Maturity Capability Model, NIST's IS MM, Open Group's ISM MM, Gartner's Security and Risk Management ML assessment, IS Risk Management Process MM, Security Incident Management Models, and IS Monitoring MM, are selected for consideration within the framework of this research.
The paper assesses the possibility of an integrated application of tests based on a statistical tool for detecting data distortions, known as Benford's Law, to detect corporate fraud. The approach has been applied as part of a forensic examination of a construction company's bona fides as a borrower. Implementation of the method allowed a fraudulent scheme associated with high tax risk activities to be exposed, while significantly reducing the workload of the audit. The effectiveness of an integrated application of Benford's Law tests has been confirmed.
A layered model of the mammalian cortex is an accepted one. One of the major challenges of using this architecture in real-life use cases is the lack of reliable implementations of the symbolic and cognitive layers. On another parallel stream, the adoption of cognitive and artificial intelligence (AI) solutions in industries has been slow. One of the reasons for this is the fact that the current generation of AI architectures does not sufficiently take care of the perception levels of the human operator. This paper presents an architecture that solves both of the above challenges. We propose a cognitive architecture where a natural-human in loop replaces most of the symbolic and cognitive layers. At the same time, we propose the use of instrumentation to measure the perceptual level of the human in real-time. This enables us to bridge the symbolic non-symbolic gap to some extent as well. Lastly, the perception-centric block also adds a novel attribute to the existing AI architectures. The current generation of AI algorithms does not incorporate the users’ perception as an integral part of the training and operation of the algorithm. To our knowledge, this is the first time user perception is an essential part of the algorithm. We call this architecture Perception-Centric Human-in-loop Cognitive Architecture (PeC-HiCA). PeC-HiCA is not only a more implementable cognitive architecture, it will also be more successful in industrial applications.
The article proposes a method for representing the economic process as a module for closing economic cycles. Such a representation is relevant for the purposes of compiling a digital map of the economic process, which can be further adjusted and supplemented with new parameters depending on the state of the external environment of the economic agent. The proposed model is universal and framework, that is, it can be used to represent any economic process in digital format without restrictions. The extension of the proposed model can be achieved by increasing the number of threads in each of the technological cycles, while each thread will have its own technological process. The practical result of the study is the compilation of a methodology that allows visualizing economic processes within a single roadmap for the entire planning horizon of the production process.
The article develops proposals for using the "economic cross" tool for the purpose of building foresight forecasts for the development of sectoral regional complexes using digital design methods. The possibilities of more complete use of the economic potential of such digital planning and modeling tools as Big Data, IoT, Sparx systems, modular digital design of business process architecture are assessed. Particular attention is paid to the aspects of using digital modeling tools for the development of an industry-based regional complex, taking into account current economic challenges. The expected results of the practical implementation of the “economic cross” modeling in the practice of designing the development of regional industry complexes will be: ensuring the complexity of assessing the system of indicators of the performance of the regional industry complex for a selected period of time, better identifying the technologies recommended for implementation in the production chains of the regional industry complex.
The goal here is to identify key directions for the future advanced research initiatives in Artificial Intelligence (AI) and beyond. The following areas are identified as having particular importance: (1) socially emotional, ethical, and moral AI, (2) self-developing and self-sustainable AI, and (3) human-analogous AI, inspired by the human psychology. As a result, a general concept is formulated with the intent to clarify and unify the currently popular slogans, including Artificial General Intelligence (AGI), Strong AI, Human-Level or Humanlike AI (HLAI), Brain-Inspired or Biologically Inspired Cognitive Architectures (BICA), and more. The key idea of the proposed concept is that future AI must open a new angle of view and new perspectives to humans, thereby enriching and transforming the society, helping it to solve its problems and taking the civilization to a new level. While being created by humans, for humans, and fully compatible with humans at the social level, it will not be “a human in silicon”, but rather an “alien”: intelligent, friendly, and welcome. Its principles will combine preprogrammed basic functions and its own natural ontogeny in a virtual social environment. Forms of implementation will range from virtual entities to wearable electronics and autonomous robots. The expected impact on the society will be immense and crucial for its survival.
The success of the developed software product largely depends on the correctly chosen architectural solution. Software architecture is a set of technical solutions that ensure that code meets the requirements of software. The growing adoption of cloud software development is bringing changes to current architectural decisions. The purpose of the article is to analyze modern architectural solutions, select the best architecture for developing a robotic system, as well as the concept of an improved solution for microservice architecture. This article covers the following architectural solutions: monolithic, service-oriented, and microservice. A solution to dividing the microservice architecture into two conceptual layers is presented, which eliminates some of the existing shortcomings. A new concept of building microservice architecture of the ALKETON robotic system is presented, which makes it easy to increase and modify the functionality, while maintaining "transparent" connections between the services of the system. A feature of this approach is the division of the microservice architecture into two conceptual layers API and APP. The developed architecture has shown high efficiency in the development of a robotic system. The designed architecture allows easy scalability due to transparent communication between microservices, which is critical in this rapidly developing industry. A robotic system ALKETON has been developed, aimed at reducing the cost of servicing front offices and attracting new customers of the age group.
A series of processes leading to dramatic changes in all aspects of our lives are ushering in the fourth industrial revolution, the foundation of which is the development of fast-growing digital technologies. Among these are big data, blockchain, artificial intelligence and neural networks, and the Internet of Things (IoT). In order to have an understanding of digital processes and their social effect, it is necessary to describe social systems and social sectors of the economy in new terms and through a new understanding of the impact of the technologies of the fourth industrial revolution. One element of such a description is the problem of developing and transforming an academic ecosystem to launch and implement interdisciplinary research projects at the intersection of the social and technical sciences. This article presents the results of methodological and informational support of designing the «Philologist Automated Workplace» as an element of academic ecosystem for launching and implementing interdisciplinary research projects at the intersection of socio-humanities and technical sciences, and formulates the following methodological recommendations for designing the concept of «Philologist Automated Workplace».
A series of processes leading to dramatic changes in all aspects of our lives are ushering in the fourth industrial revolution, the foundation of which is the development of fast-growing digital technologies. Among these are big data, blockchain, artificial intelligence and neural networks, and the Internet of Things (IoT). In order to have an understanding of digital processes and their social effect, it is necessary to describe social systems and social sectors of the economy in new terms and through a new understanding of the impact of the technologies of the fourth industrial revolution. One element of such a description is the problem of developing and transforming an academic ecosystem to launch and implement interdisciplinary projects at the intersection of the social and technical sciences. That is why we have developed the concept of the "Philologist Automated Workplace" as an element of the academic ecosystem for launching and implementing interdisciplinary research projects at the intersection of social and technical sciences.
Applications of socially emotional artificial intelligence are demanded in many practical areas, including psychological counselling and psychotherapy. A person who is potentially in trouble and needs help has to overcome an internal barrier before deciding to see a psychiatrist. On the other hand, obtaining an anonymous online consultation or taking an online test is psychologically easy and acceptable for the many. At the same time, state-of-the-art solutions of this sort are limited. Here a concept of an intelligent system is proposed that should help to alleviate the problem. The system can be implemented as an embodied actor based on a virtual environment, VR/XR, or a robotic platform with social-emotional capabilities. The actor is controlled by a cognitive architecture with a possibility of its replacement by a deep neural network model. Interaction with the user is based on a multimodal human-computer interface. Possibilities that will be provided by this virtual psychologist system will enable conducting an initial screening, the results of which can later be used at the next session with a specialist, if chosen by the user. The key issue of ethics, privacy and anonymity is discussed. Systems of this sort could be used beyond psychological counseling and are expected to have an impact on the healthcare system in general.
Thanks to the development of cloud platforms and containerization technologies, the spectrum of opportunities for deploying complex multi-component systems is extremely wide. On the one hand, the available tools unify the solution of complex problems. But on the other hand they do not have sufficient means for automatic synthesis and analysis. The article presents an approach that allows unifying and automating the task of building deployment and initialization code for of multi-component software systems. The proposed solution is based on the use of applicative computing systems and abstract algebraic structures that are interpreted in various ways to generate various parts of the software system.
In their previous studies, the authors have shown that the integration of geophysical methods allows improving the quality of the solution of an inverse problem of exploration geophysics in comparison with the individual use of each of them. However, in practice, it is possible that for some measurement points, data from one of the geophysical methods used is missing. In this study, we investigate an approach associated with neural network recovery of the missing data of one geophysical method from the known data of another, and their further joint application to solve the inverse problem. In addition, we explore the effectiveness of applying multitask learning approach at the data recovery stage for the subsequent solution of the inverse problem.
