262 search results - page 38 / 53 » Bounded-Parameter Partially Observable Markov Decision Proce... |
ML
2002
ACM
13 years 10 months ago
2002
ACM
We present new algorithms for reinforcement learning, and prove that they have polynomial bounds on the resources required to achieve near-optimal return in general Markov decisio...
AIED
2011
Springer
13 years 2 months ago
2011
Springer
Both human and automated tutors must infer what a student knows and plan future actions to maximize learning. Though substantial research has been done on tracking and modeling stu...
AAAI
2006
14 years 13 days ago
2006
Partially observable Markov decision processes (POMDPs) are an intuitive and general way to model sequential decision making problems under uncertainty. Unfortunately, even approx...
ECML
2007
Springer
14 years 5 months ago
2007
Springer
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
AI
2006
Springer
14 years 2 months ago
2006
Springer
Abstract. Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value funct...