16 search results - page 1 / 4 » No-regret learning in convex games |
MLDM
2009
Springer
13 years 11 months ago
2009
Springer
CORR
2010
Springer
13 years 4 months ago
2010
Springer
Calibrated strategies can be obtained by performing strategies that have no internal regret in some auxiliary game. Such strategies can be constructed explicitly with the use of B...
COLT
2003
Springer
13 years 10 months ago
2003
Springer
A general class of no-regret learning algorithms, called no-Φ-regret learning algorithms, is defined which spans the spectrum from no-external-regret learning to no-internal-reg...
LAMAS
2005
Springer
13 years 10 months ago
2005
Springer
We present a new multiagent learning algorithm, RVσ(t), that builds on an earlier version, ReDVaLeR . ReDVaLeR could guarantee (a) convergence to best response against stationary ...
NIPS
2004
13 years 6 months ago
2004
Learning in a multiagent system is a challenging problem due to two key factors. First, if other agents are simultaneously learning then the environment is no longer stationary, t...