453 search results - page 56 / 91 » Learning from actions not taken: a multiagent learning algor... |
ATAL
2010
Springer
14 years 10 months ago
2010
Springer
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
MICAI
2010
Springer
14 years 8 months ago
2010
Springer
The full deployment of service robots in daily activities will require the robot to adapt to the needs of non-expert users, particularly, to learn how to perform new tasks from “...
GECCO
2005
Springer
15 years 3 months ago
2005
Springer
In this paper we focus on an important source of problem– difficulty in (online) dynamic optimization problems that has so far received significantly less attention than the tr...
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
We present an algorithm, HI-MAT (Hierarchy Induction via Models And Trajectories), that discovers MAXQ task hierarchies by applying dynamic Bayesian network models to a successful...
ATAL
2003
Springer
15 years 2 months ago
2003
Springer
Multiagent learning literature has investigated iterated twoplayer games to develop mechanisms that allow agents to learn to converge on Nash Equilibrium strategy profiles. Such ...