Using the semi-tensor product（STP） of matrices, the profile evolutionary equation（PEE） for repeated finite games is obtained. By PEE, the zero-determinant（ZD） strategies are developed for general finite games. A...
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Using the semi-tensor product（STP） of matrices, the profile evolutionary equation（PEE） for repeated finite games is obtained. By PEE, the zero-determinant（ZD） strategies are developed for general finite games. A formula is then obtained to design ZD strategies for general finite games with multiple players and asymmetric strategies. A necessary and sufficient condition is obtained to ensure the availability of the designed ZD strategies. It follows that player i can unilaterally design ki-1（one less than the number of its strategies） dominating linear relations about the expected payoffs of all players. Finally, the fictitious opponent player is proposed for networked repeated games（NRGs）. A technique is proposed to simplify the model by reducing the number of frontier strategies.
In this article, the authors investigate and derive adaptive strategies for the pursuit-evasion problem where both players lack knowledge of the opponent's cost function parameters, which has rarely been investiga...
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In this article, the authors investigate and derive adaptive strategies for the pursuit-evasion problem where both players lack knowledge of the opponent's cost function parameters, which has rarely been investigated in the existing literature. To address this challenge, the authors consider a basic information structure that assumes that the evader will use an adaptive learning algorithm to estimate the unknown parameters and update its adaptive strategy piecewise, whereas the pursuer will adopt a strategy based on the opponent's choices at each time instant. By employing methods of diminishing excitation and random switching, the authors establish certain excitation conditions for signals of the closed-loop game system to ensure the strong consistency of the parameter ***, the authors demonstrate that the adaptive game system can asymptotically reach the Nash equilibrium, which is the same equilibrium achieved in pursuit-evasion games when all game parameters are known.
With the development and applications of the Smart Court System(SCS)in China,the reliability and accuracy of legal artificial intelligence have become focal points in recent ***,criminal sentencing prediction,a signif...
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With the development and applications of the Smart Court System(SCS)in China,the reliability and accuracy of legal artificial intelligence have become focal points in recent ***,criminal sentencing prediction,a significant component of the SCS,has also garnered widespread *** to the Chinese criminal law,actual sentencing data exhibits a saturated property due to statutory penalty ranges,but this mechanism has been ignored by most existing *** this,the authors propose a sentencing prediction model that combines judicial sentencing mechanisms including saturated outputs and floating boundaries with neural *** on the saturated structure of our model,a more effective adaptive prediction algorithm will be constructed based on the fusion of several key ideas and techniques that include the utilization of the L1 loss together with the corresponding gradient update strategy,a data pre-processing method based on large language model to extract semantically complex sentencing elements using prior legal knowledge,the choice of appropriate initial conditions for the learning algorithm and the construction of a double-hidden-layer network *** empirical study on the crime of disguising or concealing proceeds of crime demonstrates that our method can achieve superior sentencing prediction accuracy and significantly outperform common baseline methods.
This paper is concerned with the optimal threshold selection and resource allocation problems of quantized identification, whose aims are improving identification efficiency under limited resources. Firstly, the first...
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This paper is concerned with the optimal threshold selection and resource allocation problems of quantized identification, whose aims are improving identification efficiency under limited resources. Firstly, the first-order asymptotically optimal quantized identification theory is extended to the weak persistent excitation condition. Secondly, the characteristics of time and space complexities are established based on the Cramér-Rao lower bound of quantized systems. On these basis, the optimal selection methods of fixed thresholds and adaptive thresholds are established under aperiodic signals, which answer how to achieve the best efficiency of quantized identification under the same time and space complexity. In addition, based on the principle of maximizing the identification efficiency under a given resource, the optimal resource allocation methods of quantized identification are given for the cases of fixed thresholds and adaptive thresholds, respectively, which show how to balance time and space complexity to realize the best identification efficiency of quantized identification.
This paper focuses on the state estimate for a class of systems with both process noise and measurement noise under binary-valued observations,in which the Gaussian assumption on the predicted density of the state is ...
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This paper focuses on the state estimate for a class of systems with both process noise and measurement noise under binary-valued observations,in which the Gaussian assumption on the predicted density of the state is not required.A recursive projected filter algorithm with time-varying thresholds is constructed to estimate the state under binary-valued *** time-varying thresholds are designed as the prediction value of the measurement,which can provide more information about the system *** convergence property is established with some suitable stability,boundedness and observability *** particular,the estimation error between state and estimate is proved to be asymptotically bounded in the mean-square sense,whose upper bound is related to the variance of process ***,the theoretical results are demonstrated via numerical examples of first-order and high-order systems.
In this paper,we propose a transition system(TS)framework for the analysis and design of logical *** formula for calculating the fixed points and cycles of a TS is first ***,the TS representation of Boolean networks(B...
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In this paper,we propose a transition system(TS)framework for the analysis and design of logical *** formula for calculating the fixed points and cycles of a TS is first ***,the TS representation of Boolean networks(BNs)and Boolean control networks(BCNs)is *** first kind of representation is state-based,which converts a BCN into a TS with either distinguished controls or undistinguished *** second representation is output-based,which is also called the simulation of the original ***,after introducing the notion of output simulation,our method is applied to design output robust controls of logical networks.
In this paper,the authors consider the distributed adaptive identification problem over sensor networks using sampled data,where the dynamics of each sensor is described by a stochastic differential *** minimizing a l...
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In this paper,the authors consider the distributed adaptive identification problem over sensor networks using sampled data,where the dynamics of each sensor is described by a stochastic differential *** minimizing a local objective function at sampling time instants,the authors propose an online distributed least squares algorithm based on sampled data.A cooperative non-persistent excitation condition is introduced,under which the convergence results of the proposed algorithm are established by properly choosing the sampling time *** upper bound on the accumulative regret of the adaptive predictor can also be ***,the authors demonstrate the cooperative effect of multiple sensors in the estimation of unknown parameters by computer simulations.
This paper studies sampled-data proportional-integral(PI)control for a basic class of nonlinear uncertain *** authors claim that a process with the first-order dynamics can achieve zero steady-state error through a sa...
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This paper studies sampled-data proportional-integral(PI)control for a basic class of nonlinear uncertain *** authors claim that a process with the first-order dynamics can achieve zero steady-state error through a sampled-data PI controller whenever the sampling period Tcontroller are apparently restricted by T,or the setpoint tracking error diverges.
The paper considers the adaptive regulation for the Hammerstein and Wiener systems with event-triggered *** authors adopt a direct approach,i.e.,without identifying the unknown parameters and functions within the syst...
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The paper considers the adaptive regulation for the Hammerstein and Wiener systems with event-triggered *** authors adopt a direct approach,i.e.,without identifying the unknown parameters and functions within the systems,adaptive regulators are directly designed based on the event-triggered observations on the regulation *** adaptive regulators belong to the stochastic approximation algorithms and under moderate assumptions,the authors prove that the adaptive regulators are optimal for both the Hammerstein and Wiener systems in the sense that the squared regulation errors are asymptotically *** authors also testify the theoretical results through simulation studies.
In this paper,the authors consider the inverse problem for the Moore-Gibson-Thompson equation with a memory term and variable diffusivity,which introduce a sort of delay in the dynamics,producing nonlocal effects in *...
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In this paper,the authors consider the inverse problem for the Moore-Gibson-Thompson equation with a memory term and variable diffusivity,which introduce a sort of delay in the dynamics,producing nonlocal effects in *** H¨older stability of simultaneously determining the spatially varying viscosity coefficient and the source term is obtained by means of the key pointwise Carleman estimate for the Moore-Gibson-Thompson *** the sake of generality in mathematical tools,the analysis of this paper is discussed within the framework of Riemannian geometry.
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