Simulation-Based Optimization Algorithms For Finite-Horizon Markov Decision Processes  

Oleh:

Bhatnagar, Shalabh ; Abdulla, Mohammed Shahid

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Simulation vol. 84 no. 10-11 (Oct. 2008), page 577-600.
Topik: Finite-horizon Markov decision processes; simulation-based algorithms; two-timescale stochastic approximation; function approximation; actor-critic algorithms; normalized Hadamard matrices
Fulltext: 577.pdf (506.4KB)

Isi artikel

We develop four simulation-based algorithms for finite-horizon Markov decision processes. Two of these algorithms are developed for finite state and compact action spaces while the other two are for finite state and finite action spaces. Of the former two, one algorithm uses a linear parameterization for the policy, resulting in reduced memory complexity. Convergence analysis is briefly sketched and illustrative numerical experiments with the four algorithms are shown for a problem of flow control in communication networks.

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