86 search results - page 14 / 18 » Estimation and Approximation Bounds for Gradient-Based Reinf... |
115
Voted
ICML
2008
IEEE
16 years 2 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...
107
Voted
ICML
2004
IEEE
16 years 2 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...
120
Voted
NIPS
1998
15 years 3 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...
108
click to vote
SODA
2008
ACM
15 years 3 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-...
151
Voted
TNN
2010
14 years 8 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...