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Comparison of Evolutionary Strategies for Reinforcement Learning in a Swarm Aggregation Behaviour 20

Comparison of Evolutionary Strategies for Reinforcement Lear...

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3rd international conference on machine Learning and machine intelligence, MLMI 2020

作者： Rais Martínez, Jasmina Aznar Gregori, Fidel University of Alicante Spain

ISBN: (纸本)9781450388344

This article studies the performance of different evolutionary strategies for deep reinforcement learning policy optimization. The policy will be centred in an important swarm robotic task: the aggregation of simple robots in the environment. The main inspiration for robotic swarm comes from the observation of social animals. Ants, bees, birds, and fish are some examples of how simple individuals can succeed when they gather in groups. In addition, is important to highlight that aggregation may be considered as a previous requirement to tackle another tasks. Due the design of a swarm behaviour is a comprehensive process of experimentation, one of the current solutions is learn a policy able to control a robot. Gradient descent techniques have demonstrated their learning power in the field of neural networks and reinforcement learning, among others. But some of these techniques are difficult to be applied in the field of robotics because the requirements needed to calculate the gradient to be informative are not met. For that reason, in this article we are going to use and compare the evolutionary strategies CMA-ES, PEPG, SES, GA y OpenAI-ES. A fast simulator, based in the differential robot Mbot Ranger, will be used. Once the aggregation task is learned we will compare each strategy for different swarm sizes to analyse the convergence time, the quality of the policies, its scalability and its capacity to generalize. © 2020 ACM.

关键词： Swarm intelligence

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Congestion Control Routing Scheme for WSN using AI Technologies 3

Congestion Control Routing Scheme for WSN using AI Technolog...

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3rd international conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2024

作者： Basha, S.K. Mahaboob Gurumoorthi, E. Beulah, E. Mercy Kesavan, R. Kalaiselvan, S.A. Kumar, Lenin Tkr College of Engineering and Technology Department of Computer Science and Engineering Telangana India Cmr College of Engineering & Technology Department of Computer Science and Engineering Telangana India Vel Tech Multi Tech Dr. Rangarajan Dr.Sakunthala Engineering College Department of Computer Science and Engineering Chennai Avadi India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Chennai India Rajalakshmi Engineering College Department of Artificial Intelligence and Machine Learning Chennai India Vignan Institute of Technology and Sciences Department of Electronics Communication and Engineering Telangana India

ISBN: (纸本)9798350369083

An essential part of wireless sensor networks (WSN) is managing congestion, which occurs when the amount of traffic exceeds the combined or individual capacities of the underlying channel. As a result, developing more advanced methods to prevent, detect, and alleviate congestion requires particular considerations. In order to obtain the highest throughput, these strategies must take into account the limited resources of the WSN. Dedicated congestion control strategies and routing protocols that help in congestion detection as well as management are two of the many methods that have been created in recent years. As a means of avoiding congestion, the sink node in the previous designs would reset the topology and reduce bulk traffic. In this article, we lay the groundwork for WSNs and AI, the latter of which will try to prevent congestion in WSNs from the get-go and the former of which will try to minimize the spread of impending congestion by rerouting traffic. An integral part of modern life, Artificial intelligence (AI) allows us to create self-governing systems. It is possible to enhance performance and reliability by making use of several sophisticated AI approaches. Better network management and routing in WSN may be the outcome of studying the AI algorithm used by WSN, leading to a more dependable network. Here we'll take a look at several AI algorithms that have found their way into WSNs, and we'll talk about how these algorithms might help WSNs overcome their challenges and become more reliable and efficient. Additionally, artificial intelligence has often been disregarded in these networks because of limitations on data processing as well as power consumptions. Thanks to AI, WSN is now lightning fast, error-free, as well as effective in almost every way. Using AI methods in nodes of wireless sensors for congestion aware routes is the goal of this work. © 2024 IEEE.

关键词： Traffic congestion

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Polynomial time subgraph isomorphism algorithm for large and different kinds of graphs 3rd

Polynomial time subgraph isomorphism algorithm for large and...

引用

3rd international conference on Information and Communication Technology for Intelligent Systems, ICTIS 2018

作者： Somkunwar, Rachna Vaze, Vinod M. Shri Jagdishprasad Jhabarmal Tibrewala University JhunjhunuRajasthan333001 India

ISBN: (纸本)9789811317415

Graphs are used to represent complex structures in pattern recognition and computer vision. In various applications, these complex structures must be classified, recognized, or compared with one another. Except for special classes of graphs, graph matching has in the worst case an exponential complexity;however, there are algorithms that show an acceptable execution time, as long as the graphs are not too large. In this work, we introduce a new polynomial time algorithm for Subgraph Isomorphism, COPG algorithm, efficient for large and different kinds of graphs The Subgraph Isomorphism is used for deciding if there exist a copy of a pattern graph in a target graph. COPG algorithm is based on three phases Clustering, Optimization, and Path Generation. Performance of the new approach is based on different types of graphs, size of graphs, and number of graphs. Dataset and test set contain 10,000 numbers of graphs and subgraphs with 10,000 nodes. It also contains different graphs and subgraphs such as Generalized, M2D, M3D, and M4D. The performance of the new approach is compared with Ullman and VF series algorithms in terms of space and time complexity. © 2019, Springer Nature Singapore Pte Ltd.

关键词： pattern matching

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international conference on Reliable Software Technologies, Ada-Europe 1998

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3rd international conference on Reliable Software Technologies, Ada-Europe 1998

ISBN: (纸本)3540645365

The proceedings contain 25 papers. The special focus in this conference is on Ada 95 and Java. The topics include: Embedded opportunities;porting the GNAT tasking runtime system to the java virtual machine;automating the ada binding process for java;synchronizing multiple clients and servers;how to avoid the inheritance anomaly in ada;inside the distributed systems annex;integrating groups and transactions;implementing and using execution time clocks in ada hard real-time applications;programming hard real-time systems with optional components in ada 102;object oriented abstractions for real-time distributed systems;ada 95 for a distributed simulation system;a portable API for industrial robots;a portable testing facility for ASIS;a two-level matching mechanism for object-oriented class libraries;modern avionics requirements for the distributed systems annex;symbolic reaching definitions analysis of ada programs;looking at code with your safety goggles on and the ravenscar tasking profile for high integrity real-time programs .

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Applying Grey-Fuzzy-Fuzzy Rule to machine Vision Based Unmanned Automatic Vehicles

Applying Grey-Fuzzy-Fuzzy Rule to Machine Vision Based Unman...

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3rd international conference on Intelligent Robotics and Applications (ICIRA)

作者： Chuang, Chin-Wen Li, Jau-Rong I Shou Univ Dept Elect Engn 1Sect 1Hsueh Cheng Rd Ta Hsu Hsiang Kaohsiung Count Taiwan

ISBN: (纸本)9783642165832

The unmanned automatic vehicles (UAV) are important elements in industrial application, such as unmanned carriers in warehouse. With the great progress in the intelligent transportation systems, the UAVs are often applied to drive automatically. The mechanical vision replaces the human's eyes to be the feedback component. By the image processing, the necessary information can be figured out. However, due to the complicate calculation of image process, it will take a long calculation time from fetching image to making image information. Hence, a novel control rule that is the Grey-Fuzzy-Fuzzy controller is proposed in this paper for vision guided control of UAVs. The novel rule consists of the base-layer and upper-layer fuzzy controllers. The base-layer fuzzy controller is the classical fuzzy controller using the position error and the error difference to be the input variables. The Grey prediction is used to estimate the position error at the time of making image information. Then, the upper-layer fuzzy controller uses the two input variables, which are the estimated position error and the estimated error difference, to correct the base-layer fuzzy controller's output signal. Finally, an experimental UAV is developed to examine the potential of the proposed control scheme. The vision-based experiment of automatically driving of lane-following is carried out in this paper. The experimental results show the proposed controller will eliminate the swinging phenomenon and increase the accuracy while tracking. The experimental results also show the practical capability of the Grey-Fuzzy-Fuzzy controller.

关键词： Unmanned Automatic Vehicle Grey Theory Fuzzy Control Grey-Fuzzy-Fuzzy Control

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Finding rough set reducts with SAT

Finding rough set reducts with SAT

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10th international conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2005)

作者： Jensen, R Shen, Q Tuson, A Univ Coll Wales Dept Comp Sci Aberystwyth SY23 3BZ Dyfed Wales City Univ London Sch Informat Dept Comp London EC1V 0HB England

ISBN: (纸本)3540286535

Feature selection refers to the problem of selecting those input features that are most predictive of a given outcome;a problem encountered in many areas such as machine learning, pattern recognition and signal processing. In particular, solution to this has found successful application in tasks that involve datasets containing huge numbers of features (in the order of tens of thousands), which would be impossible to process further. Recent examples include text processing and web content classification. Rough set theory has been used as such a dataset pre-processor with much success, but current methods are inadequate at finding minimal reductions, the smallest sets of features possible. This paper proposes a technique that considers this problem from a propositional satisfiability perspective. In this framework, minimal subsets can be located and verified. An initial experimental investigation is conducted, comparing the new method with a standard rough set-based feature selector.

关键词： Rough set theory

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Multimodal real-time conversation analysis using a novel process engine

Multimodal real-time conversation analysis using a novel pro...

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international conference on Affective Computing and Intelligent Interaction and Workshops, ACII

作者： Stefan Scherer Volker Fritzsch Friedhelm Schwenker Institute of Neural Information Processing Ulm University Germany

This contribution introduces a software framework enabling researchers to develop real-time pattern recognition and sensor fusion applications in an abstraction level above that of common programming languages in order to reduce and minimize programming errors and technical obstacles. Furthermore, a proof of concept using two separate instances of the process engine on different computers with audiovisual data processing is described. The scenario shows the capability of the engine to process data in realtime and synchronously on multiple machines, which are necessary features in large scale projects.

关键词： Engines Information analysis Prototypes Java pattern analysis pattern recognition Application software Data processing Emotion recognition Automatic speech recognition

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The use of local binary pattern (LBP) feature extraction members of the mud crab genus scylla 3

The use of local binary pattern (LBP) feature extraction mem...

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3rd international conference on Advances in Artificial intelligence, ICAAI 2019

作者： Ali, Rozniza Fauzi, M. Syafieq M. Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Malaysia

ISBN: (纸本)9781450372534

In the member of mud crab, species of Scylla are the most traded seafood commodity in Asia and the culturing practice is already done in most of Asia country a few years ago. The demand for mud crabs has increased rapidly over the last decade, providing great potential for the development of the mud crab aquaculture industry. But, there is still unsolved problem where limitation of knowledge in identification is limited due to similar colours and feature characteristic. Thus, this study proposed an automatic technique that can evaluate and produce the subset of mud crab genus Scylla features by using Local Binary pattern (LBP) as a feature extraction tool. The main objective of the study is to find the optimal subset of mud crab genus Scylla features from a carapace images dataset. Based on 153 extracted features chosen by LBP features selection methods, the accuracy rates of three classification algorithms were obtained for analysis. The results from the MatLab experiment demonstrated that, the LBP method produced an accuracy under 60% for entire classifier. © 2019 ACM.

关键词： Feature extraction

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23rd international conference on Next Generation Wired/Wireless Networking, NEW2AN 2023, and 16th conference on Internet of Things and Smart Spaces, ruSMART 2023

23rd International Conference on Next Generation Wired/Wirel...

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23rd international conference on Next Generation Wired/Wireless Networking, NEW2AN 2023, and 16th conference on Internet of Things and Smart Spaces, ruSMART 2023

ISBN: (纸本)9783031609961

The proceedings contain 67 papers. The special focus in this conference is on Next Generation Wired/Wireless Networking. The topics include: Detecting PII Leakage Using DPI and machine Learning in an Enterprise Environment;deep Learning for Preventing Botnet Attacks on IoT;Design of Multi-polarisation MIMO Antenna for Heterogeneous Smartphone Applications;potential Possibilities of Voice pattern recognition by a Distributed Fiber Optic Sensor;Enhancing Wireless Connectivity Through Bayesian-Optimized UAV-BS Positioning and Charging;comparison of Centralized and Federated machine Learning Techniques for Beamtracking in 5G/6G Systems;exploring the Efficiencies and Vulnerabilities of Smart Door Control Systems: A Systematic Review;System-Level Model for SINR and HPBW Evaluation in 5G mmWave UDN with Location-Aware Beamforming;reinforcement Learning Based Power Allocation for 6G Heterogenous Networks;The Impact of Capacity Averaging in Packet-Level Modeling of 5G NR with Blockage and Micromobility;Interference Mitigation for Reconfigurable Intelligent Surface (RIS)-Aided Non-terrestrial Base Station (NTBS) in NOMA Downlink HetNets;modeling a Digital Avatar of a Car Drivers Based on the Quantification of the Information Environment;A New Blockage Detection Approach for 6G THz Systems;real-Time Anomaly Detection in Network Traffic Using Graph Neural Networks and Random Forest;addressing Security and Privacy Issues in a Smart Environment by Using Blockchain as a Preemptive Technique;the Role of Cryptocurrencies in the Development of Countries and the Fight Against Financial Problems;Designing the UzBCS Lending Platform Network Based on Blockchain Technology and Ensure Transaction Security;decentralized Blockchain Networks and Economic Security: Balancing Scalability and Security Tradeoffs;study of machine Learning Models for IoT Based Efficient Classroom Usage;transforming Higher Education: A Comprehensive Analysis of Blockchain Technologies and Digitalization.

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Recent Advances in Intelligent Informatics 1

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丛书名： Advances in Intelligent Systems and Computing

1000年

作者： Sabu M. Thampi Ajith Abraham Sankar Kumar Pal Juan Manuel Corchado Rodriguez

ISBN: (数字)9783319017785

ISBN: (纸本)9783319017778

This book constitutes the thoroughly refereed post-conference proceedings of the Second international Symposium on Intelligent Informatics (ISI 2013) held in Mysore, India during August 23-24, 2013. The 47 revised papers presented were carefully reviewed and selected from 126 initial submissions. The papers are organized in topical sections on pattern recognition, signal and image processing; data mining, clustering and intelligent information systems; multi agent systems; and computer networks and distributed systems. The book is directed to the researchers and scientists engaged in various fields of intelligent informatics.

关键词： Computational intelligence Artificial intelligence

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