109 search results - page 4 / 22 » Model Checking Markov Reward Models with Impulse Rewards |
Publication
We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
ECML
2005
Springer
14 years 3 months ago
2005
Springer
Partially Observable Markov Decision Processes (POMDP) provide a standard framework for sequential decision making in stochastic environments. In this setting, an agent takes actio...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
Abstract. Hidden Markov models are traditionally decoded by the Viterbi algorithm which finds the highest probability state path in the model. In recent years, several limitations ...
MASCOTS
1996
13 years 11 months ago
1996
Formalisms based on stochastic Petri Nets (SPNs) can employ structural analysis to ensure that the underlying stochastic process is fully determined. The focus is on the detection...
ICML
2006
IEEE
14 years 11 months ago
2006
IEEE
How should a reinforcement learning agent act if its sole purpose is to efficiently learn an optimal policy for later use? In other words, how should it explore, to be able to exp...