3 accepted papers
Effective and efficient task planning is essential for mobile robots, especially in applications like warehouse retrieval and environmental monitoring. These tasks often involve selecting one location from each of several target clusters, forming a Generalized Traveling Salesman Problem (GTSP) that…
Recent deep reinforcement learning methods have achieved remarkable success in solving multi-objective combinatorial optimization problems (MOCOPs) by decomposing them into multiple subproblems, each associated with a specific weight vector. However, these methods typically treat all subproblems equ…
Efficient and scalable adaptive traffic signal control is crucial in reducing congestion, maximizing through-put, and improving mobility experience in ever-expanding cities. Recent advances in multi-agent reinforcement learning (MARL) with parameter sharing have significantly improved the adaptive o…