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The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications.
Research & information: general --- Mathematics & science --- large margin nearest neighbor regression --- distance metrics --- prototypes --- evolutionary algorithm --- approximate differential optimization --- multiple point hill climbing --- adaptive sampling --- free radical polymerization --- autonomous driving --- object tracking --- trajectory prediction --- deep neural networks --- stochastic methods --- applied machine learning --- classification and regression --- data mining --- ensemble model --- engineering informatics --- gender-based violence in Mexico --- twitter messages --- class imbalance --- k-nearest neighbor --- instance-based learning --- graph neural network --- deep learning --- hyperparameters --- machine learning --- optimization --- inference --- metaheuristics --- animal-inspired --- exploration --- exploitation --- hot rolled strip steel --- surface defects --- defect classification --- knockout tournament --- dynamic programming algorithm --- computational complexity --- combinatorics --- intelligent transport systems --- traffic control --- spatial-temporal variable speed limit --- multi-agent systems --- reinforcement learning --- distributed W-learning --- urban motorways --- multi-agent framework --- .NET framework --- simulations --- agent-based systems --- agent algorithms --- software design --- multisensory fingerprint --- interoperability --- DeepFKTNet --- classification --- generative adversarial networks --- image classification --- transfer learning --- plastic bottle --- n/a
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Research on intelligent agents and multi-agent systems has matured during the past decade, and many effective applications of this technology are currently being deployed. Although computational approaches for multi-agent systems have mainly emerged in the past few decades, scholars have been prolific with regard to the variety of methods proposed to solve this paradigm. Different communities have emerged with multi-agent systems as their main research topic. Multi-agent systems allow the development of distributed and intelligent applications in complex and dynamic environments. Systems of this kind play a crucial role in life, evidenced by the broad range of applied areas involved in their use, including manufacturing, management sciences, e-commerce, and biotechnology. There are many reasons for the interest of researchers in this new discipline. Firstly, computational systems have gradually shifted towards a distributed paradigm where heterogeneous entities with different goals can enter and leave the system dynamically and interact with each other. Secondly, new computational systems should be able to negotiate with one another, typically on the behalf of humans, in order to come to mutually acceptable agreements. As a consequence, autonomy, interaction, mobility, and openness are key concepts studied in the area. The purpose of this book is to document some of the advances made in this paradigm and attempt to show the current state of this technology by analyzing different aspects in addition its possible application in various domains. This review of the current state-of-the-art does not intend to make an exhaustive exploration of all the current existing works but, rather, to try to give an overview of the research in agent technology, showing the high level of activity of this area.
History of engineering & technology --- multi-robot --- consensus problem --- formation control --- noise --- time delay --- unmanned surface vehicles --- multi-agent system --- training system --- genetic-based fuzzy rule learning --- intelligent autonomous control --- modeling and simulation --- multi-agent systems --- smart city development --- spatiotemporal modeling --- actor–network theory --- geoparticipation --- social interactions --- simulation model --- photovoltaic energy --- parameter fine-tuning --- self-reported behaviour --- predictive model --- multi-agent planning and scheduling --- potential game --- equilibrium selection --- interoperability --- multiagent systems --- organizational models --- agent-based collective intelligence --- multi-agent complex systems --- scale-free properties --- power law distribution --- biologically inspired approaches and methods --- collective foraging --- physics-based simulation --- methodologies for agent-based systems --- multi-robot simulation --- discrete event simulator --- agent and multi-agent applications --- classification --- prediction --- multi-agent --- wisdom-of-crowds --- Hollywood --- feature-extension --- collective-intelligence --- swarm --- educational games --- game design --- situated psychological agents --- education --- competences --- decision support system --- agent based modeling and simulation --- production scheduling --- green coffee supply chain --- agent-based modeling --- agent-based simulation --- decision support
Choose an application
Research on intelligent agents and multi-agent systems has matured during the past decade, and many effective applications of this technology are currently being deployed. Although computational approaches for multi-agent systems have mainly emerged in the past few decades, scholars have been prolific with regard to the variety of methods proposed to solve this paradigm. Different communities have emerged with multi-agent systems as their main research topic. Multi-agent systems allow the development of distributed and intelligent applications in complex and dynamic environments. Systems of this kind play a crucial role in life, evidenced by the broad range of applied areas involved in their use, including manufacturing, management sciences, e-commerce, and biotechnology. There are many reasons for the interest of researchers in this new discipline. Firstly, computational systems have gradually shifted towards a distributed paradigm where heterogeneous entities with different goals can enter and leave the system dynamically and interact with each other. Secondly, new computational systems should be able to negotiate with one another, typically on the behalf of humans, in order to come to mutually acceptable agreements. As a consequence, autonomy, interaction, mobility, and openness are key concepts studied in the area. The purpose of this book is to document some of the advances made in this paradigm and attempt to show the current state of this technology by analyzing different aspects in addition its possible application in various domains. This review of the current state-of-the-art does not intend to make an exhaustive exploration of all the current existing works but, rather, to try to give an overview of the research in agent technology, showing the high level of activity of this area.
multi-robot --- consensus problem --- formation control --- noise --- time delay --- unmanned surface vehicles --- multi-agent system --- training system --- genetic-based fuzzy rule learning --- intelligent autonomous control --- modeling and simulation --- multi-agent systems --- smart city development --- spatiotemporal modeling --- actor–network theory --- geoparticipation --- social interactions --- simulation model --- photovoltaic energy --- parameter fine-tuning --- self-reported behaviour --- predictive model --- multi-agent planning and scheduling --- potential game --- equilibrium selection --- interoperability --- multiagent systems --- organizational models --- agent-based collective intelligence --- multi-agent complex systems --- scale-free properties --- power law distribution --- biologically inspired approaches and methods --- collective foraging --- physics-based simulation --- methodologies for agent-based systems --- multi-robot simulation --- discrete event simulator --- agent and multi-agent applications --- classification --- prediction --- multi-agent --- wisdom-of-crowds --- Hollywood --- feature-extension --- collective-intelligence --- swarm --- educational games --- game design --- situated psychological agents --- education --- competences --- decision support system --- agent based modeling and simulation --- production scheduling --- green coffee supply chain --- agent-based modeling --- agent-based simulation --- decision support
Choose an application
The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications.
large margin nearest neighbor regression --- distance metrics --- prototypes --- evolutionary algorithm --- approximate differential optimization --- multiple point hill climbing --- adaptive sampling --- free radical polymerization --- autonomous driving --- object tracking --- trajectory prediction --- deep neural networks --- stochastic methods --- applied machine learning --- classification and regression --- data mining --- ensemble model --- engineering informatics --- gender-based violence in Mexico --- twitter messages --- class imbalance --- k-nearest neighbor --- instance-based learning --- graph neural network --- deep learning --- hyperparameters --- machine learning --- optimization --- inference --- metaheuristics --- animal-inspired --- exploration --- exploitation --- hot rolled strip steel --- surface defects --- defect classification --- knockout tournament --- dynamic programming algorithm --- computational complexity --- combinatorics --- intelligent transport systems --- traffic control --- spatial-temporal variable speed limit --- multi-agent systems --- reinforcement learning --- distributed W-learning --- urban motorways --- multi-agent framework --- .NET framework --- simulations --- agent-based systems --- agent algorithms --- software design --- multisensory fingerprint --- interoperability --- DeepFKTNet --- classification --- generative adversarial networks --- image classification --- transfer learning --- plastic bottle --- n/a
Choose an application
Research on intelligent agents and multi-agent systems has matured during the past decade, and many effective applications of this technology are currently being deployed. Although computational approaches for multi-agent systems have mainly emerged in the past few decades, scholars have been prolific with regard to the variety of methods proposed to solve this paradigm. Different communities have emerged with multi-agent systems as their main research topic. Multi-agent systems allow the development of distributed and intelligent applications in complex and dynamic environments. Systems of this kind play a crucial role in life, evidenced by the broad range of applied areas involved in their use, including manufacturing, management sciences, e-commerce, and biotechnology. There are many reasons for the interest of researchers in this new discipline. Firstly, computational systems have gradually shifted towards a distributed paradigm where heterogeneous entities with different goals can enter and leave the system dynamically and interact with each other. Secondly, new computational systems should be able to negotiate with one another, typically on the behalf of humans, in order to come to mutually acceptable agreements. As a consequence, autonomy, interaction, mobility, and openness are key concepts studied in the area. The purpose of this book is to document some of the advances made in this paradigm and attempt to show the current state of this technology by analyzing different aspects in addition its possible application in various domains. This review of the current state-of-the-art does not intend to make an exhaustive exploration of all the current existing works but, rather, to try to give an overview of the research in agent technology, showing the high level of activity of this area.
History of engineering & technology --- multi-robot --- consensus problem --- formation control --- noise --- time delay --- unmanned surface vehicles --- multi-agent system --- training system --- genetic-based fuzzy rule learning --- intelligent autonomous control --- modeling and simulation --- multi-agent systems --- smart city development --- spatiotemporal modeling --- actor–network theory --- geoparticipation --- social interactions --- simulation model --- photovoltaic energy --- parameter fine-tuning --- self-reported behaviour --- predictive model --- multi-agent planning and scheduling --- potential game --- equilibrium selection --- interoperability --- multiagent systems --- organizational models --- agent-based collective intelligence --- multi-agent complex systems --- scale-free properties --- power law distribution --- biologically inspired approaches and methods --- collective foraging --- physics-based simulation --- methodologies for agent-based systems --- multi-robot simulation --- discrete event simulator --- agent and multi-agent applications --- classification --- prediction --- multi-agent --- wisdom-of-crowds --- Hollywood --- feature-extension --- collective-intelligence --- swarm --- educational games --- game design --- situated psychological agents --- education --- competences --- decision support system --- agent based modeling and simulation --- production scheduling --- green coffee supply chain --- agent-based modeling --- agent-based simulation --- decision support --- multi-robot --- consensus problem --- formation control --- noise --- time delay --- unmanned surface vehicles --- multi-agent system --- training system --- genetic-based fuzzy rule learning --- intelligent autonomous control --- modeling and simulation --- multi-agent systems --- smart city development --- spatiotemporal modeling --- actor–network theory --- geoparticipation --- social interactions --- simulation model --- photovoltaic energy --- parameter fine-tuning --- self-reported behaviour --- predictive model --- multi-agent planning and scheduling --- potential game --- equilibrium selection --- interoperability --- multiagent systems --- organizational models --- agent-based collective intelligence --- multi-agent complex systems --- scale-free properties --- power law distribution --- biologically inspired approaches and methods --- collective foraging --- physics-based simulation --- methodologies for agent-based systems --- multi-robot simulation --- discrete event simulator --- agent and multi-agent applications --- classification --- prediction --- multi-agent --- wisdom-of-crowds --- Hollywood --- feature-extension --- collective-intelligence --- swarm --- educational games --- game design --- situated psychological agents --- education --- competences --- decision support system --- agent based modeling and simulation --- production scheduling --- green coffee supply chain --- agent-based modeling --- agent-based simulation --- decision support
Choose an application
The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications.
Research & information: general --- Mathematics & science --- large margin nearest neighbor regression --- distance metrics --- prototypes --- evolutionary algorithm --- approximate differential optimization --- multiple point hill climbing --- adaptive sampling --- free radical polymerization --- autonomous driving --- object tracking --- trajectory prediction --- deep neural networks --- stochastic methods --- applied machine learning --- classification and regression --- data mining --- ensemble model --- engineering informatics --- gender-based violence in Mexico --- twitter messages --- class imbalance --- k-nearest neighbor --- instance-based learning --- graph neural network --- deep learning --- hyperparameters --- machine learning --- optimization --- inference --- metaheuristics --- animal-inspired --- exploration --- exploitation --- hot rolled strip steel --- surface defects --- defect classification --- knockout tournament --- dynamic programming algorithm --- computational complexity --- combinatorics --- intelligent transport systems --- traffic control --- spatial-temporal variable speed limit --- multi-agent systems --- reinforcement learning --- distributed W-learning --- urban motorways --- multi-agent framework --- .NET framework --- simulations --- agent-based systems --- agent algorithms --- software design --- multisensory fingerprint --- interoperability --- DeepFKTNet --- classification --- generative adversarial networks --- image classification --- transfer learning --- plastic bottle --- large margin nearest neighbor regression --- distance metrics --- prototypes --- evolutionary algorithm --- approximate differential optimization --- multiple point hill climbing --- adaptive sampling --- free radical polymerization --- autonomous driving --- object tracking --- trajectory prediction --- deep neural networks --- stochastic methods --- applied machine learning --- classification and regression --- data mining --- ensemble model --- engineering informatics --- gender-based violence in Mexico --- twitter messages --- class imbalance --- k-nearest neighbor --- instance-based learning --- graph neural network --- deep learning --- hyperparameters --- machine learning --- optimization --- inference --- metaheuristics --- animal-inspired --- exploration --- exploitation --- hot rolled strip steel --- surface defects --- defect classification --- knockout tournament --- dynamic programming algorithm --- computational complexity --- combinatorics --- intelligent transport systems --- traffic control --- spatial-temporal variable speed limit --- multi-agent systems --- reinforcement learning --- distributed W-learning --- urban motorways --- multi-agent framework --- .NET framework --- simulations --- agent-based systems --- agent algorithms --- software design --- multisensory fingerprint --- interoperability --- DeepFKTNet --- classification --- generative adversarial networks --- image classification --- transfer learning --- plastic bottle
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This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019.
multi-agent systems --- agent development framework --- semantic web --- online double auction --- agent development methodology --- intelligent agents --- travel behavior --- computational accountability --- coordinated control --- directed graph --- agent methodologies --- surface vehicle --- SEA_ML --- sociogram --- formation tracking --- socio-technical systems --- agreement technologies --- electronic bartering system --- delay --- social commitments --- human-machine interaction --- regression models --- collision avoidance --- electric vehicles --- mechanism design --- model-driven development --- agent technology --- multi agent systems --- computer science --- 3D representation --- multiagent systems --- scaled consensus --- multi-agent simulation --- multiple passive agents --- type-2 fuzzy inference system --- Artificial Intelligence --- bike sharing systems (BSS) --- trajectory mining --- Mobile Robot Navigation --- open data --- RBFNNs --- agent-based programming --- methodologies for agent-based systems --- socio–technical systems --- underactuated vehicle --- BDI agents --- autonomous agents --- Behavior Trees (BTs) --- coordination models --- pedestrian environment --- person tracking --- cognitive disabilities --- coordination --- commuting --- genetic algorithm --- ontology --- Genetic Programming (GP) --- user interaction levels --- intelligent hybrid systems --- complex network --- agent-oriented technologies --- agent-based modeling --- network management --- behavior modeling --- semantic web service --- mobile communication --- smart cities --- mobile device agent --- organizational model --- [-5]agent-based simulation --- agent-based social simulation --- agent-based simulation --- data visualization --- linked data --- ambient intelligence --- orientation --- velocity obstacle --- multi-agent system --- kinodynamic planning --- agent-based modelling --- charging stations --- organizations and institutions --- agent behavior --- tree mining --- agent-oriented software engineering --- carpooling --- perishable goods
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