This paper is concerned with a class of linear-quadratic stochastic large-population problems with partial information, where the individual agent only has access to a noisy observation process related to the state. The dynamics of each agent follows a linear stochastic differential equation driven by individual noise, and all agents are coupled together via the control average term. Using the mean-field game approach and the backward separation principle with a state decomposition technique, the decentralized optimal control can be obtained in the open-loop form through a forward-backward stochastic differential equation with the conditional expectation. The optimal filtering equation is also provided. By the decoupling method, the decentralized optimal control can also be further presented as the feedback of state filtering via the Riccati equation. The explicit solution of the control average limit is given, and the consistency condition system is discussed. Moreover, the related $\varepsilon$-Nash equilibrium property is verified. To illustrate the good performance of theoretical results, an example in finance is studied.
The application of the model of geometric Brownian motion (GBM) for the problem of modeling and forecasting prices for cryptocurrencies is analyzed. For prediction the solution of the stochastic differential equation of the GBM model is used, which has a linear drift and diffusion coefficients. Different scenarios of price movement are considered.
 Keywords: geometric Brownian motion (GBM), modeling, forecasting, cryptocurrency.
Saint Petersburg SPIIRAS, A.V. Smirnov, Nikolay Teslya, Saint Petersburg SPIIRAS
During a common goal achieving, a coalition of autonomous robots may face a situation that requires prompt decision-making in order to maintain an initially agreed action plan. In this case, it is proposed to use adaptive decentralized planning mechanisms based on the model of socio-inspired self-organization and implemented using the original protocol ofnegotiations between robots. Negotiations are carried out through the execution of smart contracts that process robots' proposalsΡThe contracts are storing and distributing in a distributed ledger implemented with the HyperLedger Fabric platform.
Open access
Modular Robots and Swarm Intelligence
Advanced Research in Systems and Signal Processing