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检索条件"任意字段=6th International Workshop on Computational Logic in Mult-Agent Systems"

共 87 条记录，以下是1-10 订阅

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Fixed-Time Fault-Tolerant Control for Nonlinear multi-agent systems with Sensor and Actuator Faults 6

Fixed-Time Fault-Tolerant Control for Nonlinear Multi-Agent ...

引用

6th international Conference on Electronic Engineering and Informatics, EEI 2024

作者： Dong, Guowei Xu, Peitong College of Science Liaoning University of Technology Jinzhou China

ISBN: (纸本)9798350353594

this paper researches the fault-tolerant control (FTC) of nonlinear multi-agent systems (MASs) under sensor and actuator faults at a fixed-time. this paper studies consistency tracking problem in multi-agent in depth. Firstly, the functions of unknown nonlinear is approximated by fuzzy logic systems (FLSs) and fault compensation signals are introduced in this process to reduce the effect of sensor fault. In this process, by command filter technology to solve the problem of 'Singularity' and 'computational explosion'. then, the situation of actuator and control direction uncertainty are solved by using Nussbaum function. Finally, the stability of system is proven. Last part, simulating control strategy and illustrating effectiveness. © 2024 IEEE.

关键词： Fuzzy logic

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6th international workshop on EXplainable and TRAnsparent AI and multi-agent systems, EXTRAAMAS 2024

6th International Workshop on EXplainable and TRAnsparent AI...

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6th international workshop on EXplainable and TRAnsparent AI and multi-agent systems, EXTRAAMAS 2024

ISBN: (纸本)9783031700736

the proceedings contain 13 papers. the special focus in this conference is on EXplainable and TRAnsparent AI and multi-agent systems. the topics include: Can Interpretability Layouts Influence Human Perception of Offensive Sentences?;a Framework for Explainable multi-purpose Virtual Assistants: A Nutrition-Focused Case Study;learning Temporal Task Specifications From Demonstrations;temporal Explanations of Deep Reinforcement Learning agents;An Adaptive Interpretable Safe-RL Approach for Addressing Smart Grid Supply-Side Uncertainties;model-Agnostic Policy Explanations: Biased Sampling for Surrogate Models;explanation of Deep Learning Models via logic Rules Enhanced by Embeddings Analysis, and Probabilistic Models;py_ciu_image: A Python Library for Explaining Image Classification with Contextual Importance and Utility;towards Interactive and Social Explainable Artificial Intelligence for Digital History;Explainability and Transparency in Practice: A Comparison Between Corporate and National AI Ethics Guidelines in Germany and China;the Wildcard XAI: from a Necessity, to a Resource, to a Dangerous Decoy.

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Comparative Study of Dragonfly and Firefly Algorithms with Type-1 and Type-2 Fuzzy Parameter Adaptation 17th

Comparative Study of Dragonfly and Firefly Algorithms with T...

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17th workshop of Hybrid Intelligent systems, HIS 2024, 17th workshop on Intelligent Learning Environments, WILE 2024 and 6th workshop on New Trends in computational Intelligence and Applications, CIAPP 2024, held in conjunction with Mexican international Conference on Artificial Intelligence, MICAI 2024

作者： Guajardo, Hector M. Valdez, Fevrier Melin, Patricia Castillo, Oscar Cortes-Antonio, Prometeo Tijuana Institute of Technology TecNM Tijuana Mexico

ISBN: (纸本)9783031838781

In this paper, we studied, optimized, and compared two algorithms: Dragonfly Algorithm (DA) and the Firefly Algorithm (FA). the Dragonfly Algorithm is an optimization method based on the swarming behavior of dragonflies, mimicking behaviors such as hunting, fleeing, and swarming to explore a search space. the Firefly Algorithm, on the other hand, is based on the flashing behavior of fireflies, which use bioluminescence to communicate and attract mates. We applied Type-1 and Type-2 Fuzzy logic to both algorithms. For the Dragonfly Algorithm, we optimized the W and Beta parameters. For the Firefly Algorithm, the Beta parameter was optimized. We conducted experiments and compared the results using mathematical functions F1 to F10. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Fuzzy logic

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Learning Temporal Task Specifications From Demonstrations 6th

Learning Temporal Task Specifications From Demonstrations

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6th international workshop on Explainable and Transparent AI and multi-agent systems (EXTRAAMAS)

作者： Baert, Mattijs Leroux, Sam Simoens, Pieter Univ Ghent Dept Informat Technol IDLab IMEC Ghent Belgium

ISBN: (纸本)9783031700736;9783031700743

As we progress towards real-world deployment, the critical need for interpretability in reinforcement learning algorithms grows more pivotal, ensuring the safety and reliability of intelligent agents. this paper tackles the challenge of acquiring task specifications in linear temporal logic through expert demonstrations, aiming to alleviate the burdensome task of specification engineering. the rich semantics of temporal logics serve as an interpretable framework for delineating intricate, multi-stage tasks. We propose a method which iteratively learns a task specification and a nominal policy solving this task. In each iteration, the task specification is refined to better distinguish expert trajectories from trajectories sampled from the nominal policy. With this process we obtain a concise and interpretable task specification. Unlike previous work, our method is capable of learning directly from trajectories in the original state space and does not require predefined atomic propositions. We showcase the effectiveness of our method on multiple tasks in both an office and a Minecraft-inspired environment.

关键词： Learning From Demonstrations Linear Temporal logic Reinforcement Learning Inverse Reinforcement Learning

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Explanation of Deep Learning Models via logic Rules Enhanced by Embeddings Analysis, and Probabilistic Models 6th

Explanation of Deep Learning Models via Logic Rules Enhanced...

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6th international workshop on Explainable and Transparent AI and multi-agent systems (EXTRAAMAS)

作者： Contreras, Victor Schumacher, Michael Calvaresi, Davide Univ Appl Sci Western Switzerland HES SO Delemont Switzerland

ISBN: (纸本)9783031700736;9783031700743

Deep Learning (DL) models are increasingly dealing with heterogeneous data (i.e., a mix of structured and unstructured data), calling for adequate eXplainable Artificial Intelligence (XAI) methods. Nevertheless, only some of the existing techniques consider the uncertainty inherent to the data. To this end, this study proposes a pipeline to explain heterogeneous data-based DL models by combining embedding analysis, rule extraction methods, and probabilistic models. the proposed pipeline has been tested using synthetic data (multi-individual food items tracking). this study has achieved (i) inference enhancement through probabilistic and evidential reasoning, (ii) generation of logical explanations based on extracted rules and predictions, and (iii) integration of textual data into the explanation pipeline through embedding analysis.

关键词： XAI Deep learning Uncertainty reasoning Rule extraction Preference modeling Heterogeneous data processing

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On Efficient Single‐Core Execution of agent‐Based Epidemiological Models with Contact‐Tracing Transmission 6

On Efficient Single‐Core Execution of Agent‐Based Epidemio...

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6th international workshop on Computer Modeling and Intelligent systems, CMIS 2023

作者： Sarnatskyi, Vladyslav Baklan, Igor National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 37 Prosp. Peremohy Kyiv03056 Ukraine

In this work, we present our research on efficiency of single-core execution of agent-based epidemiological models with contact-tracing transmission. We performed an analysis of existing epidemiological agent-based modeling tools from the perspective of their performance, which reflects computational time needed to perform a single simulation step of a model with fixed number of agents. We developed several simulation algorithms, based on different model types, and showed some optimizations to maximize the performance of them. We designed a metric to compare simulation step execution times on a single CPU core and used to estimate a performance of underlying simulation algorithms in the existing methods with developed one. Even though, as it will be discussed below, it is very difficult to estimate an execution time of some algorithm without actual access to it, we present the results of our method on both modern and old CPU. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0).

关键词： computational methods

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ICECC 2023 - Proceedings of the 2023 6th international Conference on Electronics, Communications and Control Engineering

ICECC 2023 - Proceedings of the 2023 6th International Confe...

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6th international Conference on Electronics, Communications and Control Engineering, ICECC 2023

ISBN: (纸本)9798400700002

the proceedings contain 47 papers. the topics discussed include: image recognition accuracy, number of parameters and computational complexity using channel reduction by dimensional compression and attention function;face recognition (FR) integration on MABIS: a mobile automated biometric identification system for law enforcement in the Philippines;identifying users based on their activity pattern using machine learning;no reference stereoscopic video quality assessment considering self-attention and different resolution level;graph structure exploration for reinforcement learning state embedding – train Tetris agent with graph neural network;biomechanical signal measurement of the hand and condition assessment system using fuzzy logic in Parkinson’s patients;design and implementation of a portable audio signal spectrum analyzer for noise management;and mitigation of greenhouse emissions from transportation systems through modelling and data.

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6th international Conference on computational Linguistics and Intelligent systems, COLINS 2022 - Volume I: Main

作者： Yaremchuk, Svitlana Kharchenko, Vyacheslav Danube Institute of National University "Odessa Maritime Academy" 9 Fanagoriyskaya St. Izmail68600 Ukraine National Aerospace University "KhAI" 17 Chkalov St. Kharkiv61070 Ukraine

the approach to the assessment of the software reliability is described, which is based on Fuzzy logic modeling using data set of the similar software systems. the suggested Fuzzy Inference Reliability Model is based on the dependencies between the metric estimates of the complexity of modules and the number of faults. the model allows predicting the number of faults in any module of the newly developed system to perform the effective verification. the automatic extraction of fuzzy logical rules from the data set of the similar system and the import of rules into MATLAB is proposed. the automation of the modeling process would reduce the time and the effort to process large sets of experimental data. It is proposed to develop the model by increasing the number of input variables taking into account the factors of the development process affecting its reliability: the qualification of developers, the level of maturity of the development process, the degree of code reuse. © 2022 Copyright for this paper by its authors.

关键词： Software reliability

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Strategic Deductive Reasoning in Large Language Models: A Dual-agent Approach

Strategic Deductive Reasoning in Large Language Models: A Du...

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IEEE international Conference on Power, Intelligent Computing and systems (ICPICS)

作者： Siyue Li Xiaofan Zhou Zhizhong Wu Yuiian Long Yanxin Shen Northeastern University Santa Clara USA University of Florida Gainesville USA Independent Researcher Mountain View USA Independent Researcher Frisco USA Independent researcher Hangzhou China

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374322

this study explores the enhancement of deductive reasoning capabilities in Large Language Models (LLMs) through a strategic dual-agent framework. In this framework, one agent acts as a questioner and another as an answerer, with both employing advanced linguistic and logical processing to optimize information exchange. Utilizing a structured environment that limits query opportunities, our approach emphasizes the development of LLMs that can efficiently generate and interpret questions to deduce hidden information effectively. the models, which incorporate self-defined agents with a combination of pretraining and llama-3-8b enhancements, demonstrate a remarkable ability to navigate the complexities of logical deduction. Performance evaluations, based on a series of simulated interactions, illustrate the agents' improved precision and strategic acumen in narrowing down possibilities through targeted inquiries. these findings underscore the potential of LLMs in tasks requiring intricate reasoning and collaboration, marking a significant step towards more intelligent and autonomous systems.

关键词： Performance evaluation Autonomous systems Navigation computational modeling Large language models Collaboration Linguistics Probabilistic logic Cognition Problem-solving

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Optimization of Overall Generation Cost for Economic Load Dispatch using Ant-Lion Optimization Technique

Optimization of Overall Generation Cost for Economic Load Di...

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international Conference on Condition Assessment Techniques in Electrical systems (CATCON)

作者： Uday Patel Tanuj Jhankal P. N. Tekwani Amit N. Patel Kuntal Bhattacharjee Electrical Engineering Nirma University Ahmedabad India

Economic Load Dispatch (ELD) is one of the essential operation of the power system, used to save the fuel cost and efficiently meet the load demand. the issues of ELD have solved using several techniques. this work offers the resilient and efficient Ant-Lion Optimization Technique (ALOT) to solve ELD problem. the ALOT is a population-based probabilistic approach that uses the fitness function of its search agents are distributed arbitrarily throughout the search space, to direct them toward an optimal location. It also maintains note of the best outcome each search agent has been able to accomplish. the ELD problems on standard test cases under a range of constraints have been solved using ALOT technique. the proposed approach surpassed optimization strategies listed in the literature in simulations in terms of the effectiveness of the solution carried out and computational efficiency. the final results also prove the reliability of the proposed technique for the ELD problem.

关键词： Costs Sociology Probabilistic logic Power system reliability Reliability Fuels Statistics

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