Corpus ID: 16892947

Inverse Game Theory

@inproceedings{Kuleshov2015InverseGT,
  title={Inverse Game Theory},
  author={Volodymyr Kuleshov},
  year={2015}
}
One of the central questions in game theory deals with predicting the behavior of an agent. Here, we study the inverse of this problem: given the agents’ equilibrium behavior, what are possible utilities that motivate this behavior? We consider this problem in arbitrary normal-form games in which the utilities can be represented by a small number of parameters, such as in graphical, congestion, and network design games. In all such settings, we show how to efficiently, i.e. in polynomial time… Expand
7 Citations
Robust Commitments and Partial Reputation
  • PDF
Cooperative Inverse Reinforcement Learning
  • 272
  • PDF
Human-Like Motion Planning Based on Game Theoretic Decision Making
  • 24
  • PDF
Poisoning Attacks on Data-Driven Utility Learning in Games
  • 9
  • PDF
Constrained Inverse Optimal Control With Application to a Human Manipulation Task
  • 10
  • PDF
On Fighting Fire with Fire: Strategic Destabilization of Terrorist Networks
  • 2
  • PDF
Human-like Motion Planning in Populated Environments
  • PDF

References

SHOWING 1-10 OF 29 REFERENCES
Computational Rationalization: The Inverse Equilibrium Problem
  • 58
  • PDF
Empirical models of discrete games
  • 379
  • PDF
The Complexity of Rationalizing Matchings
  • 13
  • PDF
The structure and complexity of Nash equilibria for a selfish routing game
  • 273
  • PDF
Identification and Estimation of a Discrete Game of Complete Information
  • 252
  • PDF
Estimating a Game Theoretic Model
  • 13
Settling the complexity of computing two-player Nash equilibria
  • 449
  • PDF
The Complexity of Rationalizing Network Formation
  • 3
  • PDF
Calibrated Learning and Correlated Equilibrium
  • 341
A Simple Adaptive Procedure Leading to Correlated Equilibrium
  • 992
  • PDF
...
1
2
3
...