86 search results - page 14 / 18 » Estimation and Approximation Bounds for Gradient-Based Reinf... |
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
We present a reinforcement learning architecture, Dyna-2, that encompasses both samplebased learning and sample-based search, and that generalises across states during both learni...
ICML
2004
IEEE
15 years 10 months ago
2004
IEEE
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
NIPS
1998
14 years 10 months ago
1998
In this paper, we address two issues of long-standing interest in the reinforcement learning literature. First, what kinds of performance guarantees can be made for Q-learning aft...
SODA
2008
ACM
14 years 11 months ago
2008
ACM
The problem of maximizing a concave function f(x) in a simplex S can be solved approximately by a simple greedy algorithm. For given k, the algorithm can find a point x(k) on a k-...
111
Voted
TNN
2010
14 years 4 months ago
2010
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...