1235 search results - page 109 / 247 » Reinforcement learning in a nutshell |
AAAI
2008
15 years 1 months ago
2008
Potential-based shaping was designed as a way of introducing background knowledge into model-free reinforcement-learning algorithms. By identifying states that are likely to have ...
87
Voted
NIPS
2007
15 years 9 days ago
2007
We provide a provably efficient algorithm for learning Markov Decision Processes (MDPs) with continuous state and action spaces in the online setting. Specifically, we take a mo...
EUSFLAT
2001
15 years 8 days ago
2001
The correction of angular misalignment between mating components is a fundamental requirement for their successful assembly. In this paper we present how a learning agent based on...
ICML
2010
IEEE
14 years 12 months ago
2010
IEEE
We introduce new, efficient algorithms for value iteration with multiple reward functions and continuous state. We also give an algorithm for finding the set of all nondominated a...
FLAIRS
2004
15 years 9 days ago
2004
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...