CORR
2010
Springer
13 years 4 months ago
2010
Springer
We study the convergence of Markov Decision Processes made of a large number of objects to optimization problems on ordinary differential equations (ODE). We show that the optimal...
AUTOMATICA
2008
13 years 4 months ago
2008
For a countable-state Markov decision process we introduce an embedding which produces a finite-state Markov decision process. The finite-state embedded process has the same optim...
AIPS
2009
13 years 5 months ago
2009
Explaining policies of Markov Decision Processes (MDPs) is complicated due to their probabilistic and sequential nature. We present a technique to explain policies for factored MD...
ICMAS
2000
13 years 5 months ago
2000
In this paper, we formulate agent's decision process under the framework of Markov decision processes, and in particular, the multi-agent extension to Markov decision process...
ACL
2000
13 years 5 months ago
2000
Spoken dialogue managers have benefited from using stochastic planners such as Markov Decision Processes (MDPs). However, so far, MDPs do not handle well noisy and ambiguous speec...
AAAI
1998
13 years 5 months ago
1998
We present a technique for computing approximately optimal solutions to stochastic resource allocation problems modeled as Markov decision processes (MDPs). We exploit two key pro...
UAI
2004
13 years 6 months ago
2004
We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamica...
AAAI
2006
13 years 6 months ago
2006
Despite the significant progress to extend Markov Decision Processes (MDP) to cooperative multi-agent systems, developing approaches that can deal with realistic problems remains ...
IJCAI
2007
13 years 6 months ago
2007
Dynamic programming algorithms provide a basic tool identifying optimal solutions in Markov Decision Processes (MDP). The paper develops a representation for decision diagrams sui...
EXACT
2008
13 years 6 months ago
2008
There has been little work in explaining recommendations generated by Markov Decision Processes (MDPs). We analyze the difculty of explaining policies computed automatically and id...