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gTLO: A Generalized and Non-linear Multi-Objective Deep Reinforcement Learning Approach ...
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Optimal Fuzzy Controller Design for Autonomous Robot Path Tracking Using Population-Based Metaheuristics
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In: Symmetry; Volume 14; Issue 2; Pages: 202 (2022)
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Limites no emprego dos sistemas aéreos autónomos à luz do direito internacional humanitário
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Optimal Fuzzy Controller Design for Autonomous Robot Path Tracking Using Population-Based Metaheuristics
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Verification of Program Transformations with Inductive Refinement Types
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In: ISSN: 1049-331X ; ACM Transactions on Software Engineering and Methodology ; https://hal.inria.fr/hal-03518825 ; ACM Transactions on Software Engineering and Methodology, Association for Computing Machinery, 2021, 30 (1), pp.1-33. ⟨10.1145/3409805⟩ (2021)
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Double Fuzzy Probabilistic Interval Linguistic Term Set and a Dynamic Fuzzy Decision Making Model based on Markov Process with tts Application in Multiple Criteria Group Decision Making ...
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Evolution of human computer interaction
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In: Sci. Visualization ; Scientific Visualization (2021)
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Place perception from the fusion of different image representation
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In: Li, P, Li, X, Li, X, Pan, H, Khyam, MO, Noor-A-Rahim, M, Ge, SS, (2020). Place perception from the fusion of different image representation. Pattern Recognition, Vol. 110, p. 1-11 http://dx.doi.org/10.1016/j.patcog.2020.107680 (2020)
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Искусственный интеллект в задачах распознавания динамических жестов ... : Artificial Intelligence in Recognition of Dynamic Gestures ...
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Chance-Constrained Control with Lexicographic Deep Reinforcement Learning ...
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Abstract:
This paper proposes a lexicographic Deep Reinforcement Learning (DeepRL)-based approach to chance-constrained Markov Decision Processes, in which the controller seeks to ensure that the probability of satisfying the constraint is above a given threshold. Standard DeepRL approaches require i) the constraints to be included as additional weighted terms in the cost function, in a multi-objective fashion, and ii) the tuning of the introduced weights during the training phase of the Deep Neural Network (DNN) according to the probability thresholds. The proposed approach, instead, requires to separately train one constraint-free DNN and one DNN associated to each constraint and then, at each time-step, to select which DNN to use depending on the system observed state. The presented solution does not require any hyper-parameter tuning besides the standard DNN ones, even if the probability thresholds changes. A lexicographic version of the well-known DeepRL algorithm DQN is also proposed and validated via ... : published version at: https://doi.org/10.1109/LCSYS.2020.2979635 in this version we fixed a typo in (9) ...
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Keyword:
Artificial Intelligence cs.AI; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Machine Learning cs.LG; Systems and Control eess.SY
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URL: https://arxiv.org/abs/2010.09468
https://dx.doi.org/10.48550/arxiv.2010.09468
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Constraining Counterexamples in Hybrid System Falsification: Penalty-Based Approaches ...
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A Framework for Current-State Opacity under Dynamic Information Release Mechanism ...
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| 14 |
Design and Development of a New Control System for Improving Energy Efficiency and Demand Response
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Fuzzy Control Systems: Past, Present and Future
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In: ISSN: 1556-603X ; IEEE Computational Intelligence Magazine ; https://hal-uphf.archives-ouvertes.fr/hal-03644439 ; IEEE Computational Intelligence Magazine, Institute of Electrical and Electronics Engineers, 2019, 14 (1), pp.56-68. ⟨10.1109/MCI.2018.2881644⟩ (2019)
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EFFICIENT FUZZY IDENTIFICATION BASED ON INFERENCE ERROR ...
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EFFICIENT FUZZY IDENTIFICATION BASED ON INFERENCE ERROR ...
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The Need to Reconcile Concepts that Characterize Systems Withstanding Threats ...
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Global Aviation System: Towards Sustainable Development
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In: International Journal of Aviation, Aeronautics, and Aerospace (2019)
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