Markov decision processes (MDPs) have proven to be popular models for decision-theoretic planning, but standard dynamic programming algorithms for solving MDPs rely on explicit, statebased specifications and computations. To alleviate the combinatorial problems associated with such methods, we propo
β¦ LIBER β¦
Stochastic scheduling with event-based dynamic programming
β Scribed by Ger Koole
- Publisher
- Springer
- Year
- 2000
- Tongue
- English
- Weight
- 120 KB
- Volume
- 51
- Category
- Article
- ISSN
- 0340-9422
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