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Contraction theory for nonlinear stability analysis and learning-based control: A tutorial overview [PDF]
Annual Reviews in Control, 2021 Contraction theory is an analytical tool to study differential dynamics of a non-autonomous (i.e., time-varying) nonlinear system under a contraction metric defined with a uniformly positive definite matrix, the existence of which results in a necessary and sufficient characterization of incremental exponential stability of multiple solution ...
Hiroyasu Tsukamoto +2 more
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Learning-based Robust Motion Planning With Guaranteed Stability: A Contraction Theory Approach [PDF]
IEEE Robotics and Automation Letters, 2021 IEEE Robotics and Automation Letters (RA-L), Preprint Version. Accepted June, 2021 (DOI: 10.1109/LRA.2021.3091019)
Hiroyasu Tsukamoto, Soon-Jo Chung
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Evaluation of Goaf Stability Based on Transfer Learning Theory of Artificial Intelligence [PDF]
IEEE Access, 2019 Current artificial intelligence models for evaluating goaf stability in underground metal mines need a large amount of sample data for training, and their accuracy declines with small sample size. With the aim of solving this problem, this paper proposes an improved TrAdaBoost algorithm based on transfer learning theory.
Yaguang Qin +4 more
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Axioms, 2022 We show how to apply the well-known fixed-point approach in the study of the existence, uniqueness, and stability of solutions to some particular types of functional equations. Moreover, we also obtain the Ulam stability result for them. The functional equations that we consider can be used to explain various experiments in mathematical psychology and ...
Ali Turab, Janusz Brzdek, Wajahat Ali
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Existence, Uniqueness, and Stability Analysis of the Probabilistic Functional Equation Emerging in Mathematical Biology and the Theory of Learning [PDF]
Symmetry, 2021 Probabilistic functional equations have been used to analyze various models in computational biology and learning theory. It is worth noting that they are linked to the symmetry of a system of functional equations’ transformation. Our objective is to propose a generic probabilistic functional equation that can cover most of the mathematical models ...
Ali Turab, Won-Gil Park, Wajahat Ali
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The effects of spatial stability and cue type on spatial learning: Implications for theories of parallel memory systems [PDF]
Cognition, 2021 Some theories of spatial learning predict that associative rules apply under only limited circumstances. For example, learning based on a boundary has been claimed to be immune to cue competition effects because boundary information is the basis for the formation of a cognitive map, whilst landmark learning does not involve cognitive mapping.
Matt Buckley +6 more
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International Journal of Analysis and Applications, 2023 The psychological learning theory (PLT) in the formation of moral verdict is represented by the choice-practice paradigm. It involves weighing the effects of various options and choosing one to put into practice. This manuscript is devoted to presenting a general functional equation (FE) for observing animal behavior in such situations.
Doha A. Kattan, Hasanen A. Hammad
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Stability theory of game-theoretic group feature explanations for machine learning models
, 2021 82 pages, 43 figures. Typos fixed.
Miroshnikov, Alexey +3 more
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International Journal of Higher Education, 2022 Higher institutions of learning (HIL) occasionally face conflict situations. These range from minor confrontations and demonstrations to violent strikes. The aim of this study was to align theories with conflict management in HIL to avert looming crises that might affect the core businesses of HIL. Given that conflicts are miscellaneous and disputable,
Yusuf Lukman +2 more
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C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory
Advances in Neural Information Processing Systems 37Generative Adversarial Imitation Learning (GAIL) trains a generative policy to mimic a demonstrator. It uses on-policy Reinforcement Learning (RL) to optimize a reward signal derived from a GAN-like discriminator. A major drawback of GAIL is its training instability - it inherits the complex training dynamics of GANs, and the distribution shift ...
Tianjiao Luo +4 more
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