Zobrazeno 1 - 10
of 276
pro vyhledávání: '"KROESE, DIRK P."'
The Partially Observable Markov Decision Process (POMDP) provides a principled framework for decision making in stochastic partially observable environments. However, computing good solutions for problems with continuous action spaces remains challen
Externí odkaz:
http://arxiv.org/abs/2305.08049
Solving decision problems in complex, stochastic environments is often achieved by estimating the expected outcome of decisions via Monte Carlo sampling. However, sampling may overlook rare, but important events, which can severely impact the decisio
Externí odkaz:
http://arxiv.org/abs/2305.07863
Solving continuous Partially Observable Markov Decision Processes (POMDPs) is challenging, particularly for high-dimensional continuous action spaces. To alleviate this difficulty, we propose a new sampling-based online POMDP solver, called Adaptive
Externí odkaz:
http://arxiv.org/abs/2302.10439
Solving Partially Observable Markov Decision Processes (POMDPs) with continuous actions is challenging, particularly for high-dimensional action spaces. To alleviate this difficulty, we propose a new sampling-based online POMDP solver, called Adaptiv
Externí odkaz:
http://arxiv.org/abs/2209.05733
This work introduces and compares approaches for estimating rare-event probabilities related to the number of edges in the random geometric graph on a Poisson point process. In the one-dimensional setting, we derive closed-form expressions for a vari
Externí odkaz:
http://arxiv.org/abs/2007.05965