[HTML][HTML] Enhancing sparrow search algorithm via multi-strategies for continuous optimization problems
J Ma, Z Hao, W Sun - Information Processing & Management, 2022 - Elsevier
As a recent swarm intelligence optimization algorithm, sparrow search algorithm (SSA) is
widely adopted in many real-world problems. However, the solutions to the limitations of …
widely adopted in many real-world problems. However, the solutions to the limitations of …
Deployable reinforcement learning with variable control rate
D Wang, G Beltrame - ar**
large offshore wind turbine blades, and the fact that traditional game algorithms can only …
large offshore wind turbine blades, and the fact that traditional game algorithms can only …
Robot dynamics modeling with a novel friction model and extracted feasible parameters using constrained differential evolution
X Shao, L **e, C Li, Y Li - Journal of Intelligent & Robotic Systems, 2023 - Springer
Focusing on the problem of extracting a set of feasible parameters to characterize the
standard Newton-Euler (SN-E) dynamics model of robots, as an alternative to the linear …
standard Newton-Euler (SN-E) dynamics model of robots, as an alternative to the linear …
MOSEAC: Streamlined Variable Time Step Reinforcement Learning
D Wang, G Beltrame - arxiv preprint arxiv:2406.01521, 2024 - arxiv.org
Traditional reinforcement learning (RL) methods typically employ a fixed control loop, where
each cycle corresponds to an action. This rigidity poses challenges in practical applications …
each cycle corresponds to an action. This rigidity poses challenges in practical applications …
An improved multi-objective deep reinforcement learning algorithm based on envelope update
Multi-objective reinforcement learning (MORL) aims to uniformly approximate the Pareto
frontier in multi-objective decision-making problems, which suffers from insufficient …
frontier in multi-objective decision-making problems, which suffers from insufficient …