Strategically robust LQ dynamic games reduce to standard LQ games with penalized fictitious adversaries, admitting unique Markovian linear equilibria computable by coupled Riccati equations, with simulations revealing robustness benefits and a free-lunch performance improvement.
Convergent Q-learning for infinite-horizon general-sum markov games through behavioral economics
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.OC 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Strategically Robust Linear Quadratic Dynamic Games
Strategically robust LQ dynamic games reduce to standard LQ games with penalized fictitious adversaries, admitting unique Markovian linear equilibria computable by coupled Riccati equations, with simulations revealing robustness benefits and a free-lunch performance improvement.