ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1207.0852
  4. Cited By
Counter-Factual Reinforcement Learning: How to Model Decision-Makers
  That Anticipate The Future

Counter-Factual Reinforcement Learning: How to Model Decision-Makers That Anticipate The Future

3 July 2012
Ritchie Lee
David Wolpert
J. Bono
S. Backhaus
R. Bent
Brendan D. Tracey
    OffRL
ArXiv (abs)PDFHTML

Papers citing "Counter-Factual Reinforcement Learning: How to Model Decision-Makers That Anticipate The Future"

3 / 3 papers shown
Act to Reason: A Dynamic Game Theoretical Model of Driving
Act to Reason: A Dynamic Game Theoretical Model of Driving
Cevahir Köprülü
Y. Yildiz
350
1
0
14 Jan 2021
Modeling Cyber-Physical Human Systems via an Interplay Between
  Reinforcement Learning and Game Theory
Modeling Cyber-Physical Human Systems via an Interplay Between Reinforcement Learning and Game TheoryAnnual Reviews in Control (ARC), 2019
Mert Albaba
Y. Yildiz
AI4CE
124
34
0
11 Oct 2019
Cyber-Physical Security: A Game Theory Model of Humans Interacting over
  Control Systems
Cyber-Physical Security: A Game Theory Model of Humans Interacting over Control SystemsIEEE Transactions on Smart Grid (IEEE Trans. Smart Grid), 2013
S. Backhaus
R. Bent
J. Bono
Ritchie Lee
Brendan D. Tracey
David Wolpert
Dongping Xie
Y. Yildiz
180
78
0
15 Apr 2013
1
Page 1 of 1