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pro vyhledávání: '"Denkert, Robert"'
We propose a comprehensive framework for policy gradient methods tailored to continuous time reinforcement learning. This is based on the connection between stochastic control problems and randomised problems, enabling applications across various cla
Externí odkaz:
http://arxiv.org/abs/2404.17939
Autor:
Denkert, Robert, Horst, Ulrich
We establish a probabilistic framework for analysing extended mean-field games with multi-dimensional singular controls and state-dependent jump dynamics and costs. Two key challenges arise when analysing such games: the state dynamics may not depend
Externí odkaz:
http://arxiv.org/abs/2402.09317
Autor:
Denkert, Robert, Horst, Ulrich
We consider extended mean-field control problems with multi-dimensional singular controls. A key challenge when analysing singular controls are jump costs. When controls are one-dimensional, jump costs are most naturally computed by linear interpolat
Externí odkaz:
http://arxiv.org/abs/2308.04378