Results 321 to 330 of about 6,813,126 (333)
Some of the next articles are maybe not open access.
2020
Machine learning (ML) is aimed at autonomous extraction of knowledge from raw real-world data or exemplar instances. Machine learning (Barreno et al. in Proceedings of the 2006 ACM symposium on information, computer and communications security, pp 16–25, 2006 [1]) matches the learned pattern with the objects and predicts the outcome.
Nandita Sengupta, Jaya Sil
openaire +1 more source
Machine learning (ML) is aimed at autonomous extraction of knowledge from raw real-world data or exemplar instances. Machine learning (Barreno et al. in Proceedings of the 2006 ACM symposium on information, computer and communications security, pp 16–25, 2006 [1]) matches the learned pattern with the objects and predicts the outcome.
Nandita Sengupta, Jaya Sil
openaire +1 more source
2020
The purpose of the article is to analyze existing approaches of different states and actions spaces representations for Q-learning algorithm for protein structure folding problem, reveal their advantages and disadvantages and propose the new geometric ???state-space??? representation.
openaire +1 more source
The purpose of the article is to analyze existing approaches of different states and actions spaces representations for Q-learning algorithm for protein structure folding problem, reveal their advantages and disadvantages and propose the new geometric ???state-space??? representation.
openaire +1 more source
2018
In order to solve the problem that Q-learning can suffer from large overestimations in some stochastic environments, we first propose a new form of Q-learning, which proves that it is equivalent to the incremental form and analyze the reasons why the convergence rate of Q-learning will be affected by positive bias.
Zhihui Hu +3 more
openaire +1 more source
In order to solve the problem that Q-learning can suffer from large overestimations in some stochastic environments, we first propose a new form of Q-learning, which proves that it is equivalent to the incremental form and analyze the reasons why the convergence rate of Q-learning will be affected by positive bias.
Zhihui Hu +3 more
openaire +1 more source
An optimized Q-Learning algorithm for mobile robot local path planning
Knowledge-Based SystemsQian Zhou +5 more
semanticscholar +1 more source