Approximately Optimal Control of Nonlinear Dynamic Stochastic Problems with Learning: The OPTCON Algorithm

Blueschke, Dmitri; Blueschke-Nikolaeva, V.; Neck, Reinhard

doi:10.3390/a14060181

Cited by 8 publications

(5 citation statements)

References 22 publications

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“…In this study we apply the dynamic-game framework (Basar and Olsder 1999;Basar and Zaccour 2018) in order to analyze coalition strategies between the countries in a monetary union facing different shocks. The economies under consideration are described by a dynamic system of nonlinear difference equations in state-space form:…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Should fiscal policies be centralized in a monetary union? A dynamic game approach

Blueschke

Blueschke-Nikolaeva

Neck

2023

Cent Eur J Oper Res

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In this paper we analyze dynamic interactions in a monetary union with three fiscal players (the governments of the countries concerned) and a common central bank in the presence of exogenous shocks. The model is calibrated for the euro area and includes a fiscally more solid core block denoted as country 1 as well as a fiscally less solid periphery block represented by countries 2 and 3. Introducing two periphery countries allows us to capture different attitudes of the periphery countries towards the goal of sustainable fiscal performance. Moreover, different coalition scenarios are modelled in this study including a fiscal union, a coalition of periphery countries and a coalition of fiscal-stability oriented countries. The exogenous shocks are calibrated in such a way as to describe the last major crises in the euro area, namely the financial crisis, the European sovereign debt crisis, the Covid-19 crisis, and the Ukraine war (energy price) crisis. Using the OPTGAME algorithm we calculate a cooperative Pareto and non-cooperative feedback Nash equilibrium solutions for the modelled scenarios. The fully cooperative solution yields the best results. The different non-cooperative scenarios allow insights into the underlying trade-off between economic growth, price stability and fiscal stability.

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Section: Theoretical Frameworkmentioning

confidence: 99%

Should fiscal policies be centralized in a monetary union? A dynamic game approach

Blueschke

Blueschke-Nikolaeva

Neck

2023

Cent Eur J Oper Res

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“…Moreover, we consider only deterministic games. A fully stochastic analysis for a dynamic game like ours would be enormously complicated as our experiences with the single-decision maker (optimization) problem have shown (Blueschke et al 2021). Finally, one may question the assumption of the finite time horizon and introduce a scrap value, which we found not to change the strategies by much, apart from the last few periods.…”

Section: The Dynamic Game Frameworkmentioning

confidence: 99%

Macroeconomic Policy Strategies In A Monetary Union: Simulations With A Dynamic-Game Model

Blueschke¹,

Blueschke-Nikolaeva²,

Neck³

2023

ECMS 2023 Proceedings Edited by Enrico Vicario, Romeo Bandinelli, Virginia Fani, Michele Mastroianni

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We analyze alternative strategies of monetary and fiscal policies in a monetary union model with a small macroeconomic model by numerical simulations in the framework of a dynamic game. Several coalitions between governments of the member countries and the common central bank are investigated. We show that only a coalition between all governments and the central bank is efficient, while a fiscal union or other partial coalitions can be counterproductive.

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“…The following lemma is based on theory of perturbed differential equations presented in [37,39,40]: As long as it stays limited, the value hatu t i given by formula (19) together with the vehicle-speciőc parameter ξ t will converge to a recursive set of interconnected chains of traffic ŕows that are described by anomalous perturbation differential equations.…”

Section: Optimal Response Functionmentioning

confidence: 99%

An efficient algorithm for optimal route node sensing in smart tourism Urban traffic based on priority constraints

Ding,

Yao,

Khezri

2023

Wireless Netw

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The public transportation system is now dealing with a number of problems brought on by the sharp increase in automobile ownership in cities as well as the buildup of vehicles as a result of events and accidents. However, the city's limited road network capacity cannot keep up with the increasing traffic demand, which further worsens travel conditions and results in a waste of time and money. Given that it is challenging to enhance the capacity of the road network in practice, efficient vehicle travel and evacuation using algorithms has emerged as a recent study focus. It is crucial to learn how to manage urban traffic issues during emergencies and maintain smooth and safe traffic flow. The existing studies only considers the optimized route selection for individual vehicles, signal cycle of traffic lights and deploy historical data to disperse the vehicles on alternative routes. However, such works do not consider the conflict of routes between vehicles, the customized traffic demand of each vehicle and uncertain traffic conditions. Therefore, this paper proposes a novel approach to facilitate the user to select the optimal route with real-time traffic scenario. Furthermore, the Nash equilibrium is established by mutual information swapping and self-adaptive learning method. Simulation results show that the proposed algorithm has better route selection capability in real-time personalized road traffic as compared with existing algorithms.

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Approximately Optimal Control of Nonlinear Dynamic Stochastic Problems with Learning: The OPTCON Algorithm

Cited by 8 publications

References 22 publications

Should fiscal policies be centralized in a monetary union? A dynamic game approach

Should fiscal policies be centralized in a monetary union? A dynamic game approach

Macroeconomic Policy Strategies In A Monetary Union: Simulations With A Dynamic-Game Model

An efficient algorithm for optimal route node sensing in smart tourism Urban traffic based on priority constraints

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