VECTOR-VALUED MARKOV DECISION PROCESSES WITH AVERAGE REWARD
CRITERION: THE MULTICHAIN CASE
2000 ◽
Vol 14
(4)
◽
pp. 533-548
Keyword(s):
We study the multichain case of a vector-valued Markov decision process with average reward criterion. We characterize optimal deterministic stationary policies via systems of linear inequalities and discuss a policy iteration algorithm for finding all optimal deterministic stationary policies.
The policy iteration algorithm for average reward Markov decision processes with general state space
1997 ◽
Vol 42
(12)
◽
pp. 1663-1680
◽
2007 ◽
pp. 263-277
◽
1991 ◽
Vol 23
(1)
◽
pp. 193-207
◽
1999 ◽
Vol 30
(7-8)
◽
pp. 7-20
Keyword(s):