908 search results - page 53 / 182 » Stochastic Finite Learning |
NIPS
1996
13 years 10 months ago
1996
Model learning combined with dynamic programming has been shown to be e ective for learning control of continuous state dynamic systems. The simplest method assumes the learned mod...
ATAL
2004
Springer
14 years 2 months ago
2004
Springer
This paper investigates a relatively new direction in Multiagent Reinforcement Learning. Most multiagent learning techniques focus on Nash equilibria as elements of both the learn...
AAAI
2010
13 years 10 months ago
2010
Relational Markov Decision Processes (MDP) are a useraction for stochastic planning problems since one can develop abstract solutions for them that are independent of domain size ...
CORR
2008
Springer
13 years 7 months ago
2008
Springer
For a stationary stochastic process {Xn} with values in some set A, a finite word w AK is called a memory word if the conditional probability of X0 given the past is constant on t...
JMLR
2010
13 years 3 months ago
2010
Real stochastic processes operating in continuous time can be modeled by sets of stochastic differential equations. On the other hand, several popular model families, including hi...