In dynamic Stackelberg games with mid-game belief updates, assuming an incorrect follower best-response model can yield strictly lower leader cost than knowing the true model.
Algorithms for inverse reinforcement learning
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
A robot generalizes one demonstration of placing a single brick to build walls of arbitrary length and layout by approximating motions as screw sequences and using ScLERP/RMRC for planning.
citing papers explorer
-
When the Correct Model Fails: The Optimality of Stackelberg Equilibria with Follower Intention Updates
In dynamic Stackelberg games with mid-game belief updates, assuming an incorrect follower best-response model can yield strictly lower leader cost than knowing the true model.
-
Manipulation Planning for Construction Activities with Repetitive Tasks
A robot generalizes one demonstration of placing a single brick to build walls of arbitrary length and layout by approximating motions as screw sequences and using ScLERP/RMRC for planning.