arXiv subjects

Bozenna Pasik-Duncan

Publications and source records attributed to Bozenna Pasik-Duncan.

6 recordsLinked to original sources

arXiv2026

Absolute continuity of Rosenblatt measures

In the article, we address the problem of absolute continuity of translated Rosenblatt measures on the path space. In [Čoupek, P., Kříž, P., Maslowski, B., Stoch. Proc. Appl. 179 (2025) art. no. 104499], it is shown that there is no probability measure that would be equivalent to the original probability measure and under which a Rosenblatt path with a linear drift would again be a Rosenblatt path. Here, we show that if the Rosenblatt path is shifted in a direction belonging to a class of nontrivial Gaussian variables (that consists of a deterministic shift and a Wiener integral with respect to a fractional Brownian motion with a related Hurst parameter), such a measure exists. We also give several examples to demonstrate the scope of the result.

math.PR↗

arXiv2025

Mean-Field-Type Game Theory with Rosenblatt Noise

We study the integration of Rosenblatt noise into stochastic systems, control theory, and mean-field-type game theory, addressing the limitations of traditional Gaussian and Markovian models. Empirical evidence from various domains, including water demand, e-commerce, power grid operations, wireless channels, and agricultural supply chains, demonstrates the prevalence of non-Gaussian characteristics such as skews, heavy tails and strong long-range dependencies. The Rosenblatt process, a non-Gaussian non-Markovian, self-similar process, offers a baseline framework for capturing some the behaviors observed in real data. We develop novel stochastic calculus formulas for Rosenblatt processes, apply these to dynamical systems, and analyze optimal control problems, revealing the suboptimality of traditional noise approximation methods. We extend game-theoretic analysis to environments driven by Rosenblatt noise, establishing conditions for saddle-point equilibria in zero-sum games and identifying state-feedback Nash equilibria in non-zero-sum games. Our findings underscore the importance of incorporating non-Gaussian noise into predictive analytics and control strategies, enhancing the accuracy and robustness of models in real-world applications. These findings represent a significant advancement in mean-field-type game theory with variance-awareness, offering new insights and tools for managing interactive systems influenced by Rosenblatt noise.

math.OC↗

arXiv2025

Semi-Explicit Solution of Some Discrete-Time Higher-Order-Cost Mean-Field-Type Control

Traditional solvable optimal control theory predominantly focuses on quadratic costs due to their analytical tractability, yet they often fail to capture critical non-linearities inherent in real-world systems including water, energy, agriculture, and financial networks. Here, we present a unified framework for solving discrete-time optimal control with higher-order state and control costs of power-law form. By building convex-completion techniques, we derive semi-explicit expressions for control laws, cost-to-go functions, and recursive coefficient dynamics across deterministic and stochastic system settings. Key contributions include variance-aware solutions under additive and multiplicative noise, extensions to mean-field-type-dependent dynamics, and conditions that ensure the positivity of recursive coefficients. In particular, we establish that higher-order costs induce less aggressive control policies compared to quadratic formulations, a finding that is validated through numerical analyses.

math.OC↗

arXiv2025

Semi-Explicit Solution of Some Discrete-Time Mean-Field-Type Games with Higher-Order Costs

Traditional solvable game theory and mean-field-type game theory (risk-aware games) predominantly focus on quadratic costs due to their analytical tractability. Nevertheless, they often fail to capture critical non-linearities inherent in real-world systems. In this work, we present a unified framework for solving discrete-time game problems with higher-order state and strategy costs involving power-law terms. We derive semi-explicit expressions for equilibrium strategies, cost-to-go functions, and recursive coefficient dynamics across deterministic, stochastic, and multi-agent system settings by convex-completion techniques. The contributions include variance-aware solutions under additive and multiplicative noise, extensions to mean-field-type-dependent dynamics, and conditions that ensure the positivity of recursive coefficients. Our results provide a foundational methodology for analyzing non linear multi-agent systems under higher-order penalization, bridging classical game theory and mean-field-type game theory with modern computational tools for engineering applications.

math.OC↗

arXiv2019

A Stochastic Calculus for Rosenblatt Processes

A stochastic calculus is given for processes described by stochastic integrals with respect to fractional Brownian motions and Rosenblatt processes somewhat analogous to the stochastic calculus for Itô processes. These processes for this stochastic calculus arise naturally from a stochastic chain rule for functionals of Rosenblatt processes; and some Itô-type expressions are given here. Furthermore, there is some analysis of these results for their applications to problems using Rosenblatt noise.

math.PR↗

arXiv2019

Semi-Explicit Solutions to some Non-Linear Non-Quadratic Mean-Field-Type Games: A Direct Method

This article examines mean-field-type game problems by means of a direct method. We provide various solvable examples beyond the classical linear-quadratic game problems. These include quadratic-quadratic games and games with power, logarithmic, sine square, hyperbolic sine square payoffs. Non-linear state dynamics such as log-state, control-dependent regime switching, quadratic state, cotangent state and hyperbolic cotangent state are considered. We identify equilibrium strategies and equilibrium payoffs in state-and-conditional mean-field type feedback form. It is shown that a simple direct method can be used to solve broader classes of non-quadratic mean-field-type games under jump-diffusion-regime switching Gauss-Volterra processes which include fractional Brownian motions and multi-fractional Brownian motions. We provide semi-explicit solutions to the fully cooperative, noncooperative nonzero-sum, and adversarial game problems.

math.OC↗