The Accelerated Expansion of the Universe in the Light of the Maximum Ordinality Principle

The main aim of the paper is to present (and at the same time offer) a differ-ent perspective for the analysis of the accelerated expansion of the Universe. A perspective that can surely be considered as being “in parallel” to the tradition-al ones, such as those based, for example, on the hypotheses of “Dark Matter” and “Dark Energy”, or better as a “com-possible” perspective, because it is not understood as being “exclusive”. In fact, it is an approach that, when con-firmed by experimental results, always keeps its validity from an “operative” point of view. This is because, in analogy to the traditional perspectives, on the basis of Popper’s Falsification Principle the corresponding “Generative” Logic on which it is based has not the property of the perfect induction. The basic difference then only consists in the fact that the Evolution of the Universe is now modeled by considering the Universe as a Self-Organizing System, which is thus analyzed in the light of the Maximum Ordinality Principle.

A Mean-Field Stochastic Maximum Principle for Optimal Control of Forward-Backward Stochastic Differential Equations with Jumps via Malliavin Calculus

This paper considers a mean-field type stochastic control problem where the dynamics is governed by a forward and backward stochastic differential equation (SDE) driven by Lévy processes and the information available to the controller is possibly less than the overall information. All the system coefficients and the objective performance functional are allowed to be random, possibly non-Markovian. Malliavin calculus is employed to derive a maximum principle for the optimal control of such a system where the adjoint process is explicitly expressed.

Relationship between Maximum Principle and Dynamic Programming in Stochastic Differential Games and Applications

This paper is concerned with the relationship between maximum principle and dynamic programming in zero-sum stochastic differential games. Under the assumption that the value function is enough smooth, relations among the adjoint processes, the generalized Hamiltonian function and the value function are given. A portfolio optimization problem under model uncertainty in the financial market is discussed to show the applications of our result.

Maximum principle for anticipated recursive stochastic optimal control problem with delay and Lvy processes

In this paper, we study the stochastic maximum principle for optimal control prob- lem of anticipated forward-backward system with delay and Lovy processes as the random dis- turbance. This control system can be described by the anticipated forward-backward stochastic differential equations with delay and L^vy processes （AFBSDEDLs）, we first obtain the existence and uniqueness theorem of adapted solutions for AFBSDEDLs; combining the AFBSDEDLs＇ preliminary result with certain classical convex variational techniques, the corresponding maxi- mum principle is proved.

A MAXIMUM PRINCIPLE APPROACH TO STOCHASTIC H_2/H_∞ CONTROL WITH RANDOM JUMPS

A necessary maximum principle is given for nonzero-sum stochastic Oltterential games with random jumps. The result is applied to solve the H2/H∞ control problem of stochastic systems with random jumps. A necessary and sufficient condition for the existence of a unique solution to the H2/H∞ control problem is derived. The resulting solution is given by the solution of an uncontrolled forward backward stochastic differential equation with random jumps.

Necessary Maximum Principle of Stochastic Optimal Control with Delay and Jump Diffusion

In this paper, we have studied the necessary maximum principle of stochastic optimal control problem with delay and jump diffusion.

MAXIMUM PRINCIPLE FOR STOCHASTIC OPTIMAL CONTROL PROBLEM WITH DISTRIBUTED DELAYS

This paper is concerned with a Pontryagin's maximum principle for the stochastic optimal control problem with distributed delays given by integrals of not necessarily linear functions of state or control variables.By virtue of the duality method and the generalized anticipated backward stochastic differential equations,we establish a necessary maximum principle and a sufficient verification theorem.In particular,we deal with the controlled stochastic system where the distributed delays enter both the state and the control.To explain the theoretical results,we apply them to a dynamic advertising problem.

Tree Network Formation in Poisson Equation Models and the Implications for the Maximum Entropy Production Principle

This paper presents not only practical but also instructive mathematical models to simulate tree network formation using the Poisson equation and the Finite Difference Method (FDM). Then, the implications for entropic theories are discussed from the viewpoint of Maximum Entropy Production (MEP). According to the MEP principle, open systems existing in the state far from equilibrium are stabilized when entropy production is maximized, creating dissipative structures with low entropy such as the tree-shaped network. We prepare two simulation models: one is the Poisson equation model that simulates the state far from equilibrium, and the other is the Laplace equation model that simulates the isolated state or the state near thermodynamic equilibrium. The output of these equations is considered to be positively correlated to entropy production of the system. Setting the Poisson equation model so that entropy production is maximized, tree network formation is advanced. We suppose that this is due to the invocation of the MEP principle, that is, entropy of the system is lowered by emitting maximal entropy out of the system. On the other hand, tree network formation is not observed in the Laplace equation model. Our simulation results will offer the persuasive evidence that certifies the effect of the MEP principle.

ANNOUNCEMENT ON“MAXIMUM PRINCIPLE FOR NON-UNIFORMLY PARABOLIC EQUATIONS AND APPLICATIONS”

In this note we announce the global boundedness for the solutions to a class of possibly degenerate parabolic equations by De-Giorgi’s iteration.In particular,the existence of weak solutions for possibly degenerate stochastic differential equations with singular diffusion coefficients is obtained.

The Absence of “Perfect Induction”in the Science

The present paper is finalized to show that the Science, even if considered in its two different Phenomenological Approaches at present known, is unable to assert that: “Thinks are like that”. This is because both the two Scientific Approaches previously mentioned have not the property of “the perfect induction”. Consequently, although they can even reach an experimental confirmation of the theoretical results, and thus a “valid description” of the various phenomena of the surrounding world, such a description has not an “absolute value”. In fact, it always and only has an “operative validity”, that is, it exclusively and solely refers to an “experimental point of view”. This means that such an “operative validity” cannot represent the basis for a logical process characterized by a “perfect induction”. In addition, the Traditional Scientific Approach is also characterized by “Insoluble” Problems, “Intractable Problems”, Problems with “drifts”, which could generally be termed as “side effects”. On the other hand, the same com-possible Scientific Approach based on the Emerging Quality of Self-Organizing Systems, also presents its “Emerging Exits”. Consequently, none of the two mentioned scientific Approaches has the “gift” of “the perfect induction”. However, there are significant differences between the two. Differences that may “suggest” the most appropriate choice among them for an “operative point of view”. This conclusion will be com-proved by considering, with particular reference, both the “side effects”, which are related to the Traditional Approach and, on the other hand, the “Emerging Exits”, which specifically pertain to the new Scientific Approach based on the Emerging Quality of Self-Organizing Systems.

G-stochastic maximum principle for risk-sensitive control problem and its applications

This study advances the G-stochastic maximum principle(G-SMP)from a risk-neutral framework to a risk-sensitive one.A salient feature of this advancement is its applicability to systems governed by stochastic differential equations under G-Brownian motion(G-SDEs),where the control variable may influence all terms.We aim to generalize our findings from a risk-neutral context to a risk-sensitive performance cost.Initially,we introduced an auxiliary process to address risk-sensitive performance costs within the G-expectation framework.Subsequently,we established and validated the correlation between the G-expected exponential utility and the G-quadratic backward stochastic differential equation.Furthermore,we simplified the G-adjoint process from a dual-component structure to a singular component.Moreover,we explained the necessary optimality conditions for this model by considering a convex set of admissible controls.To describe the main findings,we present two examples:the first addresses the linear-quadratic problem and the second examines a Merton-type problem characterized by power utility.

Maximum principle for optimal control of neutral stochastic functional differential systems

This paper is concerned with optimal control of neutral stochastic functional differential equations(NSFDEs). The Pontryagin maximum principle is proved for optimal control, where the adjoint equation is a linear neutral backward stochastic functional equation of Volterra type(VNBSFE). The existence and uniqueness of the solution are proved for the general nonlinear VNBSFEs. Under the convexity assumption of the Hamiltonian function, a sufficient condition for the optimality is addressed as well.

Maximum Principle for Non-Zero Sum Stochastic Differential Game with Discrete and Distributed Delays

This technical note is concerned with the maximum principle for a non-zero sum stochastic differential game with discrete and distributed delays.Not only the state variable,but also control variables of players involve discrete and distributed delays.By virtue of the duality method and the generalized anticipated backward stochastic differential equations,the author establishes a necessary maximum principle and a sufficient verification theorem.To explain theoretical results,the author applies them to a dynamic advertising game problem.

A Maximum Principle for General Backward Stochastic Differential Equation

In this paper,the authors consider a stochastic control problem where the system is governed by a general backward stochastic differential equation.The control domain need not be convex,and the diffusion coefficient can contain a control variable.The authors obtain a stochastic maximum principle for the optimal control of this problem by virtue of the second-order duality method.

部分可观测带跳倒向随机系统的非零和微分博弈及其应用

微分博弈是研究两个或多个局中人的控制作用同时施加于一个由微分方程描述的动态系统时实现各自最优目标的博弈过程的理论,因其有趣的数学性质和经济领域的应用价值得到了广泛的关注。研究了一类部分可观测带跳倒向随机系统的非零和微分博弈问题,其中博弈系统涉及跳过程,且每个参与者拥有不同的观测方程。对于这种部分可观测的随机微分博弈问题,在控制域为凸的条件下,采用凸变分和对偶技术,建立了博弈纳什均衡点的最大值原理;在适当的凹凸性假设下,证明了必要性最优条件也是充分性最优条件,得到了验证定理。应用上述最大值原理,研究了部分可观测带跳倒向随机系统的线性二次(Linear Quadratic,LQ)博弈问题,得到了LQ博弈问题的唯一最优控制,其中状态方程和伴随方程构成了一类带跳的正倒向随机微分方程。由于LQ模型通常被用于描述许多金融和经济现象,期望上述的部分可观测带跳倒向随机系统的LQ博弈结果能在这些领域得到广泛应用。

企业气候信息披露制度边界与规范建构

企业气候信息披露的强化是全球趋势。从比较法的分析可以发现,现有的信息披露制度以经济层面的“重大性”为要旨,并不能充分满足企业气候信息披露的需要。企业不仅仅是市场经济活动的参与者,还是气候治理体系的重要一极,兼具气候变化治理者与被治理者的双重身份。建议企业将环境和社会的“重大性”作为信息披露的上限标准,以“最小最大值”为原则,以“最糟糕情形”为预设,从假定条件、行为准则和法律后果三方面建构相关法律规范,设计合理制度。

Stochastic global maximum principle for optimization with recursive utilities

In this paper,we study the recursive stochastic optimal control problems.The control domain does not need to be convex,and the generator of the backward stochastic differential equation can contain z.We obtain the variational equations for backward stochastic differential equations,and then obtain the maximum principle which solves completely Peng’s open problem.

Is There a Minimum Electrophilicity Principle in Chemical Reactions？

For 25 simple reactions, the changes of the hardness （△η）, polarizability （△α） and electrophilicity index （△ω） and their cube-roots （△η^1/3, △α^1/3, △ω^1/3） were calculated. It is shown that although the Maximum Hardness and Minimum Polarizability Principles are not valid for all reactions, but in most cases △ω^1/3〈0, whereas we always find △ω〈0. Our observation implies to this fact that for those chemical reactions in which the number of moles decreases or at least remains constant, the most stable species （reactants or products） have the lowest sum of electrophilicities. In other words ＂the natural direction of a chemical reaction is toward a state of minimum electrophilicity＂. This fact may be called Minimum Electrophilicity Principle （MEP）.

Mean-Field Maximum Principle for Optimal Control of Forward–Backward Stochastic Systems with Jumps and its Application to Mean-Variance Portfolio Problem

We study mean-field type optimal stochastic control problem for systems governed by mean-field controlled forward-backward stochastic differential equations with jump processes,in which the coefficients depend on the marginal law of the state process through its expected value.The control variable is allowed to enter both diffusion and jump coefficients.Moreover,the cost functional is also of mean-field type.Necessary conditions for optimal control for these systems in the form of maximum principle are established by means of convex perturbation techniques.As an application,time-inconsistent mean-variance portfolio selectionmixed with a recursive utility functional optimization problem is discussed to illustrate the theoretical results.

求解多维背包的改进差分进化算法

针对多维背包问题,提出了一种改进的差分进化(IDE)算法。该算法保留了基本差分进化算法的交叉策略,同时将特定维数的0-1变异融入其中;为提高算法的收敛性,设计了最大和最小可装入背包的物品数量模型,作为对后续操作产生解的一个条件判断,从而缩小了搜索范围及时间;最后,通过对10个背包测试集进行测试,并与贪心二进制狮群优化(GBLSO)算法、混合粒子群(HPSO)算法进行比较。结果表明,该算法能较好的求得最优解,具有更快的收敛速度及更高的精度。