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Guest Editorial computational and artificial intelligence in High Speed Networks

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IEEE Journal on Selected Areas in Communications 1997年第2期15卷 133-135页

作者： I.W. Habib R.J.T. Morris H. Saito B. Pherson Electrical Engineering Department of the City College of New York

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Ant colony optimization -: artificial ants as a computational intelligence technique

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IEEE computational intelligence MAGAZINE 2006年第4期1卷 28-39页

作者： Dorigo, Marco Birattari, Mauro Stuetzle, Thomas Univ Libre Bruxelles Brussels Belgium

From the early nineties, when the first Ant colony optimization algorithm was proposed, ACO attracted the attention of increasing numbers of researchers and many successful applications are now available. [...] a substantial corpus of theoretical results is becoming available that provides useful guidelines to researchers and practitioners in further applications of ACO.

关键词： Ant colony optimization Bridges Insects Fluctuations computational intelligence computational and artificial intelligence Competitive intelligence Problem-solving Animals Guidelines

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MLHOps: Machine Learning Health Operations

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IEEE ACCESS 2025年 13卷 20374-20412页

作者： Khattak, Faiza Khan Subasri, Vallijah Krishnan, Amrit Pou-Prom, Chloe Akinli-Kocak, Sedef Dolatabadi, Elham Pandya, Deval Seyyed-Kalantari, Laleh Rudzicz, Frank Vector Inst Toronto ON M5G 0C6 Canada Vector Inst Artificial Intelligence Toronto ON M5G 1M1 Canada Hosp Sick Children Genet & Genome Biol Canad Toronto ON M5G 1E8 Canada Univ Toronto Dept Med Biophys Toronto ON M5S 1A1 Canada Univ Hlth Network Peter Munk Cardiac Ctr Toronto ON M5G 2N2 Canada St Michaels Hosp Toronto ON M5B 1W8 Canada York Univ Sch Hlth Policy & Management Toronto ON M3J 1P3 Canada York Univ Lassonde Sch Engn Toronto ON M3J 1P3 Canada Dalhousie Univ Fac Comp Sci Halifax NS B3H 4R2 Canada

Machine Learning Health Operations (MLHOps) is the combination of processes for reliable, efficient, usable, and ethical deployment and maintenance of machine learning models in healthcare settings. This paper provides both a survey of work in this area and guidelines for developers and clinicians to deploy and maintain their own models in clinical practice. We cover the foundational concepts of general machine learning operations and describe the initial setup of MLHOps pipelines (including data sources, preparation, engineering, and tools). We then describe long-term monitoring and updating (including data distribution shifts and model updating) and ethical considerations (including bias, fairness, interpretability, and privacy). This work therefore provides guidance across the full pipeline of MLHOps from conception to initial and ongoing deployment. We also include a checklist to ensure thorough verification of each step in the process.

关键词： Pipelines Data models Machine learning Monitoring Training Standards Predictive models Hospitals Production Metadata computational and artificial intelligence machine learning engineering in medicine and biology electronic healthcare health information management hospitals

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A Fuzzy Purpose-in-Life Perspective for artificial intelligence, Robotics and computational intelligence

A Fuzzy Purpose-in-Life Perspective for Artificial Intellige...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ernesto Araujo Integration and Testing Laboratory (LIT) National Institute of Space Research (INPE) Sao Paulo Brazil

A fuzzy mechanism for building a goal-driven, life-purpose perspective for artificial intelligence, robotics or computational intelligence is presented in this paper. According to a non-traditional epistemological paradigm for understanding the term intelligence this adaptive fuzzy goal-driven approach becomes an alternative both to construct intelligent systems and to understand human intelligence. The fuzzy system as suggested may yet be seen as a useful mechanism for representing the approximate human-being reasoning due the likelihood it presents when compared to the way human beings adapt their reasoning and behavior in order to accommodate small changes caused by the environment or by the context. In this sense the proposed approach may also allow the nature of intelligent machine and intelligent human behavior converge to be the same.

关键词： artificial intelligence Intelligent robots computational intelligence Competitive intelligence computational and artificial intelligence Humans Fuzzy systems Machine intelligence Buildings Intelligent systems

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artificial immune systems - a new emerging technology of computational intelligence - implications on development of the autonomous intelligent systems, data mining and other hybrid intelligent systems

Artificial immune systems - a new emerging technology of com...

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International Conference on Telecommunications (ConTEL)

作者： M.G.H. Negoita School of Information Technology Wellington Institute of Technology Wellington New Zealand

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A Brief Overview of artificial intelligence Focusing on computational Models of Emotions

A Brief Overview of Artificial Intelligence Focusing on Comp...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Brigitte Lorenz Etienne Barnard Université de Nice Sophia-Antipolis CNRS France College of Marine Engineering Northwestern Polytechnical University Xian China

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Multi-Fidelity Sensor Selection: Greedy Algorithms to Place Cheap and Expensive Sensors With Cost Constraints

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IEEE SENSORS JOURNAL 2021年第1期21卷 600-611页

作者： Clark, Emily Brunton, Steven L. Kutz, J. Nathan Univ Washington Dept Phys Seattle WA 98195 USA Univ Washington Dept Mech Engn Seattle WA 98195 USA Univ Washington Dept Appl Math Seattle WA 98195 USA

We develop greedy algorithms to approximate the optimal solution to the multi-fidelity sensor selection problem, which is a cost constrained optimization problem prescribing the placement and number of cheap (low signal-to-noise) and expensive (high signal-to-noise) sensors in an environment or state space. Specifically, we evaluate the composition of cheap and expensive sensors, along with their placement, required to achieve accurate reconstruction of a high-dimensional state. We use the column-pivoted QR decomposition to obtain preliminary sensor positions. How many of each type of sensor to use is highly dependent upon the sensor noise levels, sensor costs, overall cost budget, and the singular value spectrum of the data measured. Such nuances allow us to provide sensor selection recommendations based on computational results for asymptotic regions of parameter space. We also present a systematic exploration of the effects of the number of modes and sensors on reconstruction error when using one type of sensor. Our extensive exploration of multi-fidelity sensor composition as a function of data characteristics is the first of its kind to provide guidelines towards optimal multi-fidelity sensor selection.

关键词： Sensor phenomena and characterization Noise level Sensor systems Matrix decomposition Noise measurement Guidelines computational and artificial intelligence computational intelligence computation theory greedy algorithms sensors sensor phenomena and characterization sensor systems and applications sensor arrays signal processing noise additive noise

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Hybrid Sense Classification Method for Large-Scale Word Sense Disambiguation

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IEEE ACCESS 2020年 8卷 27247-27256页

作者： Heo, Yoonseok Kang, Sangwoo Seo, Jungyun Sogang Univ Dept Comp Sci & Engn Seoul 04107 South Korea Gachon Univ Dept Software Gyeonggi 13120 South Korea

Word sense disambiguation (WSD) is a task of determining a reasonable sense of a word in a particular context. Although recent studies have demonstrated some progress in the advancement of neural language models, the scope of research is still such that the senses of several words can only be determined in a few domains. Therefore, it is necessary to move toward developing a highly scalable process that can address a lot of senses occurring in various domains. This paper introduces a new large WSD dataset that is automatically constructed from the Oxford Dictionary, which is widely used as a standard source for the meaning of words. We propose a new WSD model that individually determines the sense of the word in accordance with its part of speech in the context. In addition, we introduce a hybrid sense prediction method that separately classifies the less frequently used senses for achieving a reasonable performance. We have conducted comparative experiments to demonstrate that the proposed method is more reliable compared with the baseline approaches. Also, we investigated the adaptation of the method to a realistic environment with the use of news articles.

关键词： computational and artificial intelligence English vocabulary learning natural language processing neural networks word sense disambiguation

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A General Dichotomy of Evolutionary Algorithms on Monotone Functions

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IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 2020年第6期24卷 995-1009页

作者： Lengler, Johannes Swiss Fed Inst Technol Dept Comp Sci CH-8092 Zurich Switzerland

It is known that the (1 + 1)-EA with mutation rate c/n optimizes every monotone function efficiently if c = 2.2. We study the same question for a large variety of algorithms, particularly for the (1 + lambda)-EA, (mu ... 详细信息

It is known that the (1 + 1)-EA with mutation rate c/n optimizes every monotone function efficiently if c < 1, and needs exponential time on some monotone functions (HOTTOPIC functions) if c >= 2.2. We study the same question for a large variety of algorithms, particularly for the (1 + lambda)-EA, (mu + 1)-EA, (mu + 1)-GA, their "fast" counterparts, and for the (1 + (lambda, lambda))-GA. We find that all considered mutation-based algorithms show a similar dichotomy for HOTTOPIC functions, or even for all monotone functions. For the (1 + (lambda, lambda))-GA, this dichotomy is in the parameter c gamma, which is the expected number of bit flips in an individual after mutation and crossover, neglecting selection. For the fast algorithms, the dichotomy is in m(2)/m(1), where m(1) and m(2) are the first and second falling moment of the number of bit flips. Surprisingly, the range of efficient parameters is not affected by either population size mu nor by the offspring population size lambda. The picture changes completely if crossover is allowed. The genetic algorithms (mu + 1)-GA and (mu+1)-fGA are efficient for arbitrary mutations strengths if mu is large enough.

关键词： Runtime Evolutionary computation Genetic algorithms Sociology Statistics Heuristic algorithms Standards computational and artificial intelligence evolutionary computation genetic algorithms

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Conceptual Game Expansion

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IEEE TRANSACTIONS ON GAMES 2022年第1期14卷 93-106页

作者： Guzdial, Matthew Riedl, Mark O. Univ Alberta Alberta Machine Intelligence Inst Dept Comp Sci Edmonton AB T6G 0T3 Canada Georgia Inst Technol Sch Interact Comp Atlanta GA 30332 USA

Automated game design is the problem of automatically producing games through computational processes. Traditionally, these methods have relied on the authoring of search spaces by a designer, defining the space of all possible games for the system to the author. In this article, we instead learn representations of existing games from gameplay video and use these to approximate a search space of novel games. In a human subject study, we demonstrate that these novel games are indistinguishable from human games in terms of challenge and that one of the novel games was equivalent to one of the human games in terms of fun, frustration, and likeability.

关键词： Games Creativity Machine learning Training Knowledge based systems Automobiles Training data computational and artificial intelligence design tools electronic design methodology knowledge representation machine learning (ML) pattern analysis procedural content generation

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