Reinforcement learning (RL) applications require a huge effort to become established in real-
world environments, due to the injury and break down risks during interactions between the …

The latest achievements in the field of reinforcement learning have encouraged the
development of vision-based learning methods that compete with human-provided results …

In the realm of artificial intelligence and card games, this study introduces a two-step
reinforcement learning (RL) strategy tailored for" The Lord of the Rings: The Card Game …

Policy gradient (PG) is a reinforcement learning (RL) approach that optimizes a
parameterized policy model for an expected return using gradient ascent. While PG can …

Construction robotics, while steadily gaining research traction, encounter practical
constraints limiting widespread adoption, with challenges stemming from the dynamic nature …

Machine learning involves many challenging integrals that can be estimated using
numerical methods. One application of these methods which has been explored in recent …