Abstract
This is an overview paper on the relationship between risk-averse designs based on exponential loss functions with or without an additional unknown (adversarial) term and some classes of stochastic games. In particular, the paper discusses the equivalences between risk-averse controller and filter designs and saddle-point solutions of some corresponding risk-neutral stochastic differential games with different information structures for the players. One of the by-products of these analyses is that risk-averse controllers and filters (or estimators) for control and signal-measurement models are robust, through stochastic dissipation inequalities, to unmodeled perturbations in controlled system dynamics as well as signal and the measurement processes. The paper also discusses equivalences between risk-sensitive stochastic zero-sum differential games and some corresponding risk-neutral three-player stochastic zero-sum differential games, as well as robustness issues in stochastic nonzero-sum differential games with finite and infinite populations of players, with the latter belonging to the domain of mean-field games.
Original language | English (US) |
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Pages (from-to) | 1634-1665 |
Number of pages | 32 |
Journal | Journal of Systems Science and Complexity |
Volume | 34 |
Issue number | 5 |
DOIs | |
State | Published - Oct 2021 |
Keywords
- Mean-field games
- risk sensitivity
- risk-sensitive control
- risk-sensitive filtering
- risk-sensitive games
- robustness
ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Information Systems