scholarly journals Volatility of Volatility: A Simple Model-Free Motivation

Wilmott ◽  
2012 ◽  
Vol 2012 (61) ◽  
pp. 64-67
Author(s):  
Gabriel G. Drimus
Keyword(s):  
IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 4351-4363
Author(s):  
Ansei Yonezawa ◽  
Itsuro Kajiwara ◽  
Heisei Yonezawa

2019 ◽  
Author(s):  
Carolina Feher da Silva ◽  
Todd A. Hare

AbstractDistinct model-free and model-based learning processes are thought to drive both typical and dysfunctional behaviours. Data from two-stage decision tasks have seemingly shown that human behaviour is driven by both processes operating in parallel. However, in this study, we show that more detailed task instructions lead participants to make primarily model-based choices that have little, if any, simple model-free influence. We also demonstrate that behaviour in the two-stage task may falsely appear to be driven by a combination of simple model-free and model-based learning if purely model-based agents form inaccurate models of the task because of misconceptions. Furthermore, we report evidence that many participants do misconceive the task in important ways. Overall, we argue that humans formulate a wide variety of learning models. Consequently, the simple dichotomy of model-free versus model-based learning is inadequate to explain behaviour in the two-stage task and connections between reward learning, habit formation, and compulsivity.


2019 ◽  
Vol 146 ◽  
pp. 156-160 ◽  
Author(s):  
Xiaolin Chen ◽  
Yahui Zhang ◽  
Xiaojing Chen ◽  
Yi Liu

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Huanhuan Mai ◽  
Ying-Jeh Huang ◽  
Xiaofeng Liao ◽  
Ping-Chou Wu

A simple model-free controller is presented for solving the nonlinear dynamic control problems. As an example of the problem, a planetary gear-type inverted pendulum (PIP) is discussed. To control the inherently unstable system which requires real-time control responses, the design of a smart and simple controller is made necessary. The model-free controller proposed includes a swing-up controller part and a stabilization controller part; neither controller has any information about the PIP. Since the input/output scaling parameters of the fuzzy controller are highly sensitive, we use genetic algorithm (GA) to obtain the optimal control parameters. The experimental results show the effectiveness and robustness of the present controller.


2020 ◽  
Vol 87 ◽  
pp. 1-16 ◽  
Author(s):  
B. Kamaruddin ◽  
H. Zabiri ◽  
A.A.A. Mohd Amiruddin ◽  
W.K. Teh ◽  
M. Ramasamy ◽  
...  

Author(s):  
Chunhong Zheng ◽  
Yuxin Su ◽  
Paolo Mercorelli

Abstract This paper revisits the problem of global asymptotic positioning of uncertain motion systems subject to actuator constraint and friction. A simple model-free saturated control is proposed by incorporating a relay term driven by position error into proportional-derivative (PD) methodology. Lyapunov's direct method is employed to prove global asymptotic positioning stability. The appealing advantages of the proposed approach are that it is conceived within the framework of saturated PD (SPD) control methodology with intuitive structure and absence of modeling parameter and embeds the whole control action within a single saturation function. Benefitted from these advantages, the proposed approach omits the complicated discrimination of the terms that shall be bounded in several saturation functions of the commonly used design and permits easy implementation with an improved performance. An additive feature is that the proposed control has the ability to ensure that the actuator constraint is not breached and assures global asymptotic positioning stability in the presence of unknown friction. Numerical simulations and experimental validations demonstrate the effectiveness and improved performance of the proposed approach. The proposed approach provides a model-free solution for fast transient and high-precision steady-state positioning of uncertain motion systems subject to unknown friction and actuator constraint.


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