ML Anthology

Solving MDPs with Skew Symmetric Bilinear Utility Functions

Hugo Gilbert, Olivier Spanjaard, Paolo Viappiani, Paul Weng
IJCAI 2015 pp. 1989-1995
/ijcai/2015/gilbert2015ijcai-solving/

Abstract

In this paper we adopt Skew Symmetric Bilinear (SSB) utility functions to compare policies in Markov Decision Processes (MDPs). By considering pairs of alternatives, SSB utility theory generalizes von Neumann and Morgenstern's expected utility (EU) theory to encompass rational decision behaviors that EU cannot accommodate. We provide a game-theoretic analysis of the problem of identifying an SSB-optimal policy in finite horizon MDPs and propose an algorithm based on a double oracle approach for computing an optimal (possibly randomized) policy. Finally, we present and discuss experimental results where SSB-optimal policies are computed for a popular TV contest according to several instantiations of SSB utility functions.

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Cite

Text

Gilbert et al. "Solving MDPs with Skew Symmetric Bilinear Utility Functions." International Joint Conference on Artificial Intelligence, 2015.

Markdown

[Gilbert et al. "Solving MDPs with Skew Symmetric Bilinear Utility Functions." International Joint Conference on Artificial Intelligence, 2015.](https://mlanthology.org/ijcai/2015/gilbert2015ijcai-solving/)

BibTeX

@inproceedings{gilbert2015ijcai-solving,
  title     = {{Solving MDPs with Skew Symmetric Bilinear Utility Functions}},
  author    = {Gilbert, Hugo and Spanjaard, Olivier and Viappiani, Paolo and Weng, Paul},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2015},
  pages     = {1989-1995},
  url       = {https://mlanthology.org/ijcai/2015/gilbert2015ijcai-solving/}
}