Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Dernedde, Tim"'
Autor:
Dernedde, Tim, Thyssens, Daniela, Dittrich, Sören, Stubbemann, Maximilian, Schmidt-Thieme, Lars
Relevant combinatorial optimization problems (COPs) are often NP-hard. While they have been tackled mainly via handcrafted heuristics in the past, advances in neural networks have motivated the development of general methods to learn heuristics from
Externí odkaz:
http://arxiv.org/abs/2402.04915
Neural Combinatorial Optimization has been researched actively in the last eight years. Even though many of the proposed Machine Learning based approaches are compared on the same datasets, the evaluation protocol exhibits essential flaws and the sel
Externí odkaz:
http://arxiv.org/abs/2310.04140
Autor:
Bdeir, Ahmad, Boeder, Simon, Dernedde, Tim, Tkachuk, Kirill, Falkner, Jonas K., Schmidt-Thieme, Lars
In this paper we present a new approach to tackle complex routing problems with an improved state representation that utilizes the model complexity better than previous methods. We enable this by training from temporal differences. Specifically Q-Lea
Externí odkaz:
http://arxiv.org/abs/2104.12226