Work

MDAC: Multi-Agent Distributional Soft Actor-Critic with Attention for Warehouse Task Coordination

Year: 2025

Type: conference-paper

Abstract: In this paper, we introduce a groundbreaking extension to the Soft Actor-Critic (SAC) algorithm, called Multi-Agent Distributional Soft Actor-Critic (MDAC), specifically tailored to enhance multi-agent coordination in dynamic warehouse environments. The core innovation of MDAC lies in the use of a distributional critic network, which predicts the full distribution of Q-values rather than just their expected values. This approach enables more robust decision-making and fosters improved exploration in complex scenarios.

Source: International Conference on Computer Information and Big Data Applications (CIBDA)

DOI: 10.1145/3746709.3746860

Authors: Yihang Xu, Kai Zheng, Qiuxia Wang

Institution: Chongqing University of Posts and Telecommunications

Language: English

Topic: Reinforcement Learning in Robotics

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4413812541

FWCI: 1.059

Cites: 1

Cited by: 1

Related to: 10