8 search results - page 1 / 2 » Regret Minimization in Games with Incomplete Information |
NIPS
2007
13 years 6 months ago
2007
Extensive games are a powerful model of multiagent decision-making scenarios with incomplete information. Finding a Nash equilibrium for very large instances of these games has re...
UAI
2004
13 years 6 months ago
2004
Mechanism design has found considerable application to the construction of agent-interaction protocols. In the standard setting, the type (e.g., utility function) of an agent is n...
SOFSEM
2010
Springer
14 years 1 months ago
2010
Springer
Regret minimization has proven to be a very powerful tool in both computational learning theory and online algorithms. Regret minimization algorithms can guarantee, for a single de...
ATAL
2010
Springer
13 years 5 months ago
2010
Springer
Games are used to evaluate and advance Multiagent and Artificial Intelligence techniques. Most of these games are deterministic with perfect information (e.g. Chess and Checkers)....
AAAI
2012
11 years 7 months ago
2012
In large extensive form games with imperfect information, Counterfactual Regret Minimization (CFR) is a popular, iterative algorithm for computing approximate Nash equilibria. Whi...