Sciweavers

Share
AAAI
2012

Competing with Humans at Fantasy Football: Team Formation in Large Partially-Observable Domains

8 years 8 months ago
Competing with Humans at Fantasy Football: Team Formation in Large Partially-Observable Domains
We present the first real-world benchmark for sequentiallyoptimal team formation, working within the framework of a class of online football prediction games known as Fantasy Football. We model the problem as a Bayesian reinforcement learning one, where the action space is exponential in the number of players and where the decision maker’s beliefs are over multiple characteristics of each footballer. We then exploit domain knowledge to construct computationally tractable solution techniques in order to build a competitive automated Fantasy Football manager. Thus, we are able to establish the baseline performance in this domain, even without complete information on footballers’ performances (accessible to human managers), showing that our agent is able to rank at around the top percentile when pitched against 2.5M human players.
Tim Matthews, Sarvapali D. Ramchurn, Georgios Chal
Added 29 Sep 2012
Updated 29 Sep 2012
Type Journal
Year 2012
Where AAAI
Authors Tim Matthews, Sarvapali D. Ramchurn, Georgios Chalkiadakis
Comments (0)
books