Theoretical Artificial Intelligence Research Articles

Analysis of nanomedicine production via green processing: Modeling and simulation of pharmaceutical solubility using artificial intelligence

This research focuses on investigating the solubility of tolfenamic acid in SC-CO2 (supercritical carbon dioxide) and the density of SC-CO2 solvent via theoretical artificial intelligence method. The study involves analyzing the relationship between temperature, pressure, and the corresponding mentioned outputs for the process. Three different predictive models, namely Multi-layer Perceptron (MLP), Polynomial Regression (PR), and Extra Trees (ET) are utilized to forecast the solubility of drug and the density of solvent (SC–CO2). The models are fine-tuned with hyper-parameters using the Dragonfly Algorithm (DA) to ensure accurate predictions. The solubility prediction is remarkably accurate using the MLP model, showing a high score of 0.98329 in terms of R-squared. The maximum error is 0.2474, and the MAE is 0.1095, demonstrating the model's high precision in estimating tolfenamic acid's solubility in SC-CO2. The PR model demonstrates exceptional accuracy, yielding a score of 0.99844 by R-squared metric, a maximum error of 0.068, and an MAE of 0.0314. The ET model also performs well, with an R-squared score of 0.90977, a maximum error of 0.445, and an MAE of 0.1665. Regarding density prediction, MLP outperforms the other techniques, achieving a significant R2 parameter of 0.99919, an MSE of 12.663, and a mean MAPE of 0.0037.

Artificial Intelligence in Dentistry: Literature Review

Artificial Intelligence has exploded as a research subject in the 21st century as the hardware requirements of theoretical Artificial intelligence in the 19th and 20th century have translated into reality. This has led to rapid progress with the realization of multiple kinds of neural networks, as well as improvements along classical Machine Learning models like Decision Trees, Support Vector Machines etc. Most recently, the focus in Machine Learning has now shifted towards generative networks with Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs) leading modern research topics.
 With advent of the Internet of Medical Things (IoMT) and modern time leaps in the domain of Artificial Intelligence with the explosion of Machine and Deep Learning, Medical AI has grasped the central stage in modern research. Applications of Medical AI vary from detections of various cancerous tumors to prediction of arrhythmia attacks. The augmentation of such AI embedded techniques into the medical profession has streamlined analysis as well as aided professionals in reaching a more efficient and accurate diagnosis. This has also translated in the field of dentistry where strong deep learning architectures such as Convolutional neural networks in the form of Resnet, Inception, GoogleNet etc have been used to process raw images and detect a range of dental diseases.
 This paper aims to provide an overview of progress made in the field of Machine Learning particularly focusing on its medical and dental applications. Different facets of Machine Learning are discussed with respect to their strengths, shortcomings, and the way artificial intelligence has been used to tackle problems in the medical field. Finally, a descriptive overview about state-of-the-art machine learning reliant applications that are being used in different dental subfields is discussed along with current challenges the industry faces today.

Replica Symmetry Breaking in Dense Hebbian Neural Networks

Understanding the glassy nature of neural networks is pivotal both for theoretical and computational advances in Machine Learning and Theoretical Artificial Intelligence. Keeping the focus on dense associative Hebbian neural networks, the purpose of this paper is two-fold: at first we develop rigorous mathematical approaches to address properly a statistical mechanical picture of the phenomenon of {\em replica symmetry breaking} (RSB) in these networks, then -- deepening results stemmed via these routes -- we aim to inspect the {\em glassiness} that they hide. In particular, regarding the methodology, we provide two techniques: the former is an adaptation of the transport PDE to the case, while the latter is an extension of Guerra's interpolation breakthrough. Beyond coherence among the results, either in replica symmetric and in the one-step replica symmetry breaking level of description, we prove the Gardner's picture and we identify the maximal storage capacity by a ground-state analysis in the Baldi-Venkatesh high-storage regime. In the second part of the paper we investigate the glassy structure of these networks: in contrast with the replica symmetric scenario (RS), RSB actually stabilizes the spin-glass phase. We report huge differences w.r.t. the standard pairwise Hopfield limit: in particular, it is known that it is possible to express the free energy of the Hopfield neural network as a linear combination of the free energies of an hard spin glass (i.e. the Sherrington-Kirkpatrick model) and a soft spin glass (the Gaussian or "spherical" model). This is no longer true when interactions are more than pairwise (whatever the level of description, RS or RSB): for dense networks solely the free energy of the hard spin glass survives, proving a huge diversity in the underlying glassiness of associative neural networks.

Application of Artificial Intelligence in Digital Games Based on Mathematical Statistics

Digital games are various games designed and developed with digital technology and implemented on digital equipment. With the active development of the modern game industry, related technologies such as real-time graphics rendering, realistic interaction, and artificial intelligence of games are also constantly improving. Among them, the artificial intelligence technology of games is limited by the development of theoretical artificial intelligence and the calculation time of real-time systems, and the development lags behind graphics and interactive technology. In order to solve these problems, this paper proposes the application of artificial intelligence in digital games based on mathematical statistics methods, aimed at studying and improving the intelligence level of digital games. The method of this paper is to study the mathematical statistics method and the basic principle of Sarsa learning algorithm and then propose the technology of artificial intelligence applied to digital games. The role of these methods is to study different types of mathematical statistics, to study the behavioral tree of artificial intelligence in digital games and the development prospects of the game, and to update the value of artificial intelligence in each iteration according to the Sarsa algorithm formula. This paper proposes a decision-making system to improve the intelligence level of digital games by analyzing the research status of digital games and the mathematical statistics of basketball digital games. In the basketball game experiment, the difference between the operation data of the decision-making system proposed in this paper and the operation data of human players in five game items reaches 0.51, 0.83, 0.58, 0.49, and 0.78, respectively.

Mental Perturbance

Understanding intrusive mentation, rumination, obsession, and worry, known also as "repetitive thought" (RT), is important for understanding cognitive and affective processes in general. RT is of transdiagnostic significance—for example obsessive-compulsive disorder, insomnia and addictions involve counterproductive RT. It is also a key but under-acknowledged feature of emotional episodes. We argue that RT cannot be understood in isolation but must rather be considered within models of whole minds and for this purpose we suggest an integrative design-oriented (IDO) approach. This approach involves the design stance of theoretical Artificial Intelligence (the central discipline of cognitive science), augmented by systematic conceptual analysis, aimed at explaining how autonomous agency is possible. This requires developing, exploring and implementing cognitive-affective-conative information-processing architectures. Empirical research on RT and emotions needs to be driven by such theories, and theorizing about RT needs to consider such data. Mental perturbance is an IDO concept that, we argue, can help characterize, explain, and theoretically ground the concept of RT. Briefly, perturbance is a mental state in which motivators tend to disrupt, or otherwise influence, executive processes even if reflective processes were to try to prevent or minimize the motivators’ influence. We draw attention to an IDO architecture of mind, H-CogAff, to illustrate the IDO approach to perturbance. We claim, further, that the intrusive mentation of some affective states— including grief and limerence (the attraction phase of romantic love) — should be conceptualized in terms of perturbance and the IDO architectures that support perturbance. We call for new taxonomies of RT and emotion in terms of IDO architectures such as H-CogAff. We point to areas of research in psychology that would benefit from the concept of perturbance.

COVID-19 (Coronavirus Disease 2019): Opportunities and Challenges for Digital Health and the Internet of Medical Things in China.

OMICS: A Journal of Integrative BiologyVol. 24, No. 5 EditorialsCOVID-19 (Coronavirus Disease 2019): Opportunities and Challenges for Digital Health and the Internet of Medical Things in ChinaBiaoyang Lin and ShengJun WuBiaoyang LinAddress correspondence to: Biaoyang Lin, PhD, Department of Urology, University of Washington School of Medicine, Seattle, WA 98195, USA E-mail Address: biaoylin@gmail.comZhejiang-California International Nanosystems Institute (ZCNI) Proprium Research Center, Zhejiang University, Hangzhou, China.Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.Department of Urology, University of Washington School of Medicine, Seattle, Washington, USA.Search for more papers by this author and ShengJun WuDepartment of Clinical Laboratories, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China.Search for more papers by this authorPublished Online:7 May 2020https://doi.org/10.1089/omi.2020.0047AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"COVID-19 (Coronavirus Disease 2019): Opportunities and Challenges for Digital Health and the Internet of Medical Things in China." OMICS: A Journal of Integrative Biology, 24(5), pp. 231–232FiguresReferencesRelatedDetailsCited byEmerging technologies for COVID (ET-CoV) detection and diagnosis: Recent advancements, applications, challenges, and future perspectivesBiomedical Signal Processing and Control, Vol. 83Integration of cloud computing with the Internet of things for the treatment and management of the COVID-19 pandemic15 November 2022 | Information Systems and e-Business Management, Vol. 26A novel e-healthcare diagnosing system for COVID-19 via whale optimization algorithm24 September 2022 | Journal of Experimental & Theoretical Artificial Intelligence, Vol. 6Call for Papers: COVID-19 Systems Biology, Multi-Omics Integration, and Digital Technologies in Ecology, Health, and Society Vural Özdemir7 September 2022 | OMICS: A Journal of Integrative Biology, Vol. 26, No. 9From Personalized Medicine to Population Health: A Survey of mHealth Sensing TechniquesIEEE Internet of Things Journal, Vol. 9, No. 17The role of contemporary digital tools and technologies in COVID‐19 crisis: An exploratory analysis6 October 2021 | Expert Systems, Vol. 39, No. 6Coronavirus Disease (COVID-19): Challenges and Opportunities10 September 2020 | Disaster Medicine and Public Health Preparedness, Vol. 16, No. 2Anthropomorphic Robotic Eyes: Structural Design and Non-Verbal Communication Effectiveness15 April 2022 | Sensors, Vol. 22, No. 8Digital Transformation in Personalized Medicine with Artificial Intelligence and the Internet of Medical Things Biaoyang Lin and Shengjun Wu7 February 2022 | OMICS: A Journal of Integrative Biology, Vol. 26, No. 2A Review About the Main Technologies to Fight COVID-1915 April 2022Identifying and addressing digital health risks associated with emergency pandemic response: Problem identification, scoping review, and directions toward evidence-based evaluationInternational Journal of Medical Informatics, Vol. 157Unlocking the Public Perception of COVID-19 Vaccination Process on Social MediaToward Combatting COVID-19: A Risk Assessment SystemIEEE Internet of Things Journal, Vol. 8, No. 21An online COVID-19 self-assessment framework supported by IoMT technology6 August 2021 | Journal of Intelligent Systems, Vol. 30, No. 1A Security Management Framework for Big Data in Smart HealthcareBig Data Research, Vol. 25Connected Medical Kiosks to Counter COVID-19: Needs, Architecture & Design GuidelinesThe perspectives of biomarker-based electrochemical immunosensors, artificial intelligence and the Internet of Medical Things toward COVID-19 diagnosis and managementMaterials Today Chemistry, Vol. 20Internet of Things (IoT) Enabled Architecture for Social Distancing During Pandemic15 April 2021 | Frontiers in Communications and Networks, Vol. 2A Comprehensive Review of Applications of Internet of Things for Covid-19 PandemicIOP Conference Series: Materials Science and Engineering, Vol. 1055, No. 1Robotics and Drone-Based Solution for the Impact of COVID-19 Worldwide Using AI and IoT16 February 2021Digital Transformation and Emerging Technologies for COVID-19 Pandemic: Social, Global, and Industry Perspectives20 February 2021Telemedicine maybe an effective solution for management of chronic disease during the COVID-19 epidemic29 September 2021 | Primary Health Care Research & Development, Vol. 22Uma análise sobre o desenvolvimento de tecnologias digitais em saúde para o enfrentamento da COVID-19 no Brasil e no mundo1 January 2021 | Cadernos de Saúde Pública, Vol. 37, No. 3Enabled IoT Applications for Covid-191 May 2021Swarm Intelligence based Hierarchical Routing Protocols Study in WSNsCOVID-19 Digital Health Innovation Policy: A Portal to Alternative Futures in the Making Mustafa Bayram, Simon Springer, Colin K. Garvey, and Vural Özdemir3 August 2020 | OMICS: A Journal of Integrative Biology, Vol. 24, No. 8Digital Technologies-Enabled Smart Manufacturing and Industry 4.0 in the Post-COVID-19 Era: Lessons Learnt from a Pandemic3 July 2020 | International Journal of Environmental Research and Public Health, Vol. 17, No. 13Adoption of Digital Technologies in Health Care During the COVID-19 Pandemic: Systematic Review of Early Scientific Literature6 November 2020 | Journal of Medical Internet Research, Vol. 22, No. 11 Volume 24Issue 5May 2020 InformationCopyright 2020, Mary Ann Liebert, Inc., publishersTo cite this article:Biaoyang Lin and ShengJun Wu.COVID-19 (Coronavirus Disease 2019): Opportunities and Challenges for Digital Health and the Internet of Medical Things in China.OMICS: A Journal of Integrative Biology.May 2020.231-232.http://doi.org/10.1089/omi.2020.0047Published in Volume: 24 Issue 5: May 7, 2020Online Ahead of Print:April 20, 2020PDF download

Why Taddeo and Floridi did not solve the symbol grounding problem

The symbol grounding problem (SGP), which remains difficult for AI and philosophy of information, was recently scrutinised by Taddeo and Floridi (Solving the symbol grounding problem: A critical review of fifteen years of research. Journal of Experimental & Theoretical Artificial Intelligence, 17, 419–445, 2005; A praxical solution of the symbol grounding problem. Minds and machines, 17, 369–389, doi:10.1007/s11023-007-9081-32005, 2007). However, their own solution to SGP, underwritten by Action-based Semantics, although different from other solutions, does not seem to be satisfactory. Moreover, it does not satisfy the authors' principle, which they dub ‘Zero Semantic Commitment Condition’. In this paper, Taddeo and Floridi's solution is criticised in particular because of the excessively liberal relationship between symbols and internal states of agents, which is conceived in terms of levels of abstraction. Also, the notion of action seems to be seriously defective in their theory. Due to the lack of the possibility of symbols to misrepresent, the grounded symbols remain useless for the cognitive system itself, and it is unclear why they should be grounded in the first place, as the role of grounded symbols is not specified by the proposed solution. At the same time, it is probably one of the best-developed attempts to solve SGP and shows that naturalised semantics can benefit from taking artificial intelligence seriously.

Categorizing entities by common role

Many categories group together entities that play a common role across situations. For example, guest and host refer to complementary roles in visiting situations and, thus, are role-governed categories (A. B. Markman & Stilwell, Journal of Experiment & Theoretical Artificial Intelligence, 13, 329-358, 2001). However, categorizing an entity by role is one of many possible classification strategies. This article examines factors that promote role-governed categorization over thematic-relation-based categorization (Lin & Murphy, Journal of Experimental Psychology: General, 130, 3-28, 2001). In Experiments 1a and 1b, we demonstrate that the use of novel category labels facilitates role-governed categorization. In Experiments 2a and 2b, we demonstrate that analogical comparison facilitates role-governed categorization. In Experiments 1b and 2b, we show that these facilitatory factors induce a general sensitivity to role information, as opposed to only promoting role-governed categorization on an item-by-item basis.

Employing emotions to drive plot generation in a computer-based storyteller

Emotions are an integral part of the creative process; however, it is hard to find computer models of creativity where emotions play a fundamental role. This paper describes a computer model for plot generation based on emotions and tensions between characters. In particular, the document illustrates how emotions are employed to progress a story in a coherent way and generate novel situations, and how the dramatic tension of the story in progress can be employed to evaluate its interestingness. The model is implemented in a computer program named MEXICA [Pérez y Pérez, R., & Sharples, M. (2001). MEXICA: a computer model of a cognitive account of creative writing. Journal of Experimental and Theoretical Artificial Intelligence, 13(2), 119–139]; this work concentrates on the role of emotions in plot generation. The main claim is that a story can be represented as a cluster or group of emotional links and tensions between characters that progresses over story-time; story-actions work as operators that modify such clusters. I present results showing how story generation is affected by various model parameters. This approach means the program is flexible, as it avoids using predefined story-structures or characters’ goals to drive story generation. Furthermore, evaluation of computer generated stories showed that MEXICA’s stories were most often selected as the best story. This suggests that the story-generation mechanisms within MEXICA are sufficiently rich to generate interesting and novel stories.

Introduction concept lattice-based theory, methods and tools for knowledge discovery in databases: Applications

Concept or Galois Lattices (CL) provide a productive framework for a variety of problems that arise in Knowledge Discovery in Databases (KDD). This paper introduces this special issue of Applied Artificial Intelligence devoted to applications of Concept Lattices for KDD (CLKDD). The papers in this volume come from a call for papers issued after the first International Workshop on Concept Lattice-based Theory, Methods and Tools for KDD held in July 2001 at Stanford University. Another special issue devoted to algorithms and methods of CLKDD will appear in the Journal of Experimental and Theoretical Artificial Intelligence.

Concept lattice-based knowledge discovery in databases

(2002). Concept lattice-based knowledge discovery in databases. Journal of Experimental & Theoretical Artificial Intelligence: Vol. 14, No. 2-3, pp. 75-79.

Why Turing machine equivalence is (still) important in cognitive science: a reply to Eliasmith

(2002). Why Turing machine equivalence is (still) important in cognitive science: a reply to Eliasmith. Journal of Experimental & Theoretical Artificial Intelligence: Vol. 14, No. 1, pp. 9-12.

Homo sapiens 2.0: why we should build the better robots of our nature

(2001). Homo sapiens 2.0: why we should build the better robots of our nature. Journal of Experimental & Theoretical Artificial Intelligence: Vol. 13, No. 4, pp. 323-328.

The case against AI from imagistic expertise

(1996). The case against AI from imagistic expertise. Journal of Experimental & Theoretical Artificial Intelligence: Vol. 8, No. 3-4, pp. 383-397.

PREFACE

International Journal of Cooperative Information SystemsVol. 01, No. 01, pp. 1-4 (1992) No AccessPREFACEhttps://doi.org/10.1142/S0218215792000167Cited by:8 Next AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail Remember to check out the Most Cited Articles! Check out these titles in digital security! FiguresReferencesRelatedDetailsCited By 8BELIEF REVISION FOR ADAPTIVE INFORMATION FILTERING AGENTSRAYMOND LAU, ARTHUR H. M. TER HOFSTEDE, and PETER D. BRUZA1 May 2012 | International Journal of Cooperative Information Systems, Vol. 10, No. 01n02An Aristotelian understanding of object-oriented programmingDerek Rayside and Gerard T. Campbell1 October 2000 | ACM SIGPLAN Notices, Vol. 35, No. 10Correctness issues in workflow managementMohan Kamath and Krithi Ramamritham1 January 1999 | Distributed Systems Engineering, Vol. 3, No. 4Putting objects to work on a massive scaleMichael L. Brodie1 June 2005Database: Introduction to problemsKeith G. Jeffery6 June 2005A model for heterogeneous distributed database systemsKeith G. Jeffery, Liz Hutchinson, John Kalmus, Michael Wilson and Wernher Behrendt et al.31 May 2005Representing reified relations in LoomROBERT M. MACGREGOR1 Apr 1993 | Journal of Experimental & Theoretical Artificial Intelligence, Vol. 5, No. 2-3The promise of distributed computing and the challenges of legacy systemsMichael L. Brodie1 June 2005 Recommended Vol. 01, No. 01 Metrics History PDF download

Norms of Cooperation

A longstanding tradition in the social sciences contrasts instrumental rationality and social norms as alternative ways of explaining action. Rational choice theory defines action as the outcome of a practical inference that takes preferences and beliefs as premises. An explanation in terms of norms depicts a socialized actor whose behavior is not outcome oriented, since when acting in accordance with a norm one does not engage in a rational calculation nor does one pay very much attention to the consequences. Attempts at bridging the gap have either tried to establish that social norms are rational, in the sense of being efficient means to achieve individual or social welfare, or that it is rational to conform to norms, thus reducing compliance to utility maximization. The first reductionist strategy makes a typical post hoc, ergo propter hoc fallacy, since the mere presence of a social norm does not justify inferring that it is there to accomplish some social function. Besides, it does not account for the fact that many social norms are inefficient, as in the case of discriminatory norms against women and blacks, or are so rigid as to prevent the fine-tuning that would be necessary to successfully accommodate new cases. Even if a norm is a means to achieve a social end, such as cooperation, retribution, or fairness, usually it is not the sole means. Many social norms are underdetermined with respect to the collective objectives they may serve, nor can they be ordered according to a criterion of greater or lesser efficiency in meeting these goals. Such an ordering would be feasible only if it were possible to show that one norm among others is the best means to attain a given social objective. Often, though, the objectives themselves are defined by means of some norm. Consider as an example norms of revenge; until not long ago, a Sicilian man who "dishonored" another man's daughter or sister had to make amends for the wrong by marrying the woman or pay for his rashness with his own life. The objective was to restore the family's lost

Searle's extension of the Chinese room to connectionist machines

(1990). Searle's extension of the Chinese room to connectionist machines. Journal of Experimental & Theoretical Artificial Intelligence: Vol. 2, No. 2, pp. 185-187.

Decomposing meat: a commentary on Sticklen's ‘problem-solving architecture at the knowledge level’

(1989). Decomposing meat: a commentary on Sticklen's ‘problem-solving architecture at the knowledge level’. Journal of Experimental & Theoretical Artificial Intelligence: Vol. 1, No. 4, pp. 259-262.

Experimental and theoretical artificial intelligence

Abstract