Multi-Edge Was Always Right—It Was Just Out Of Reach

Multi-edge delivery promised resilience and performance, but complexity held it back. New orchestration models are turning a ...
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Multi-constraint reinforcement learning in complex robot environments

FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.
IEEE

Preference-Based Multi-Objective Reinforcement Learning

Abstract: Multi-objective reinforcement learning (MORL) is a structured approach for optimizing tasks with multiple objectives. However, it often relies on pre-defined reward functions, which can be ...
IEEE

Multi-Objective Optimization Algorithms for Energy Management System in Microgrids Including Control Strategy

Renewable energy (RE) offers a promising solution to address the electricity shortages in isolated and rural areas. Microgrid (MG) can incorporate various energy sources, including renewable ...