Gambler bandits and the regret of being ruined
In this paper we consider a particular class of problems called multiarmed gambler bandits
(MAGB) which constitutes a modified version of the Bernoulli MAB problem where two new …
(MAGB) which constitutes a modified version of the Bernoulli MAB problem where two new …
Learning intrinsically motivated options to stimulate policy exploration
A Reinforcement Learning (RL) agent needs to find an optimal sequence of actions in order
to maximize rewards. This requires consistent exploration of states and action sequences to …
to maximize rewards. This requires consistent exploration of states and action sequences to …
Mixed Time-Frame Training for Reinforcement Learning
G Senthilnathan - 2022 21st IEEE International Conference on …, 2022 - ieeexplore.ieee.org
Reinforcement learning typically only uses one type of environment during training: episodic
or non-episodic. In this paper, we propose a novel training technique, Mixed Time-Frame …
or non-episodic. In this paper, we propose a novel training technique, Mixed Time-Frame …
[PDF][PDF] HAL Id: hal-03120813 https://hal. archives-ouvertes. fr/hal-03120813
In this paper we consider a particular class of problems called multiarmed gambler bandits
(MAGB) which constitutes a modified version of the Bernoulli MAB problem where two new …
(MAGB) which constitutes a modified version of the Bernoulli MAB problem where two new …
Exploration et Exploitation dans des MDPs Cybernétiques
FS Perotto - 10èmes Journées Francophones sur la Planification, la …, 2015 - hal.science
Dans cet article on présente l'algorithme" average engaged climber"(AEC), une version
modifiée de la méthode d'itération sur les valeurs pour l'estimation de la fonction d'utilité …
modifiée de la méthode d'itération sur les valeurs pour l'estimation de la fonction d'utilité …