101 search results - page 6 / 21 » Multi-task reinforcement learning: a hierarchical Bayesian a... |
NIPS
1997
14 years 11 months ago
1997
We present a new approach to reinforcement learning in which the policies considered by the learning process are constrained by hierarchies of partially specified machines. This ...
IROS
2009
IEEE
15 years 4 months ago
2009
IEEE
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
ICANN
2009
Springer
15 years 1 months ago
2009
Springer
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
ATAL
2004
Springer
15 years 3 months ago
2004
Springer
Research on coalition formation usually assumes the values of potential coalitions to be known with certainty. Furthermore, settings in which agents lack sufficient knowledge of ...
ICML
2010
IEEE
14 years 10 months ago
2010
IEEE
We are interested in learning programs for multiple related tasks given only a few training examples per task. Since the program for a single task is underdetermined by its data, ...