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NIPS
2008
14 years 18 days ago
Biasing Approximate Dynamic Programming with a Lower Discount Factor
Most algorithms for solving Markov decision processes rely on a discount factor, which ensures their convergence. It is generally assumed that using an artificially low discount f...
Marek Petrik, Bruno Scherrer
FOSSACS
2007
Springer
14 years 5 months ago
Approximating a Behavioural Pseudometric Without Discount for Probabilistic Systems
Desharnais, Gupta, Jagadeesan and Panangaden introduced a family of behavioural pseudometrics for probabilistic transition systems. These pseudometrics are a quantitative analogue ...
Franck van Breugel, Babita Sharma, James Worrell