BDI Agents Based Dynamic Resource Allocation in Emergency Scenarios

This study proposes a dynamic resource scheduling framework based on a multi-agent system (MAS). The framework integrates the Belief-Desire-Intention model with fuzzy logic and time windows to enable efficient dynamic resource allocation. It is designed to address various uncertainties in emergency resource allocation, such as delays in data transmission and sudden changes in the external environment. These uncertainties impact the efficiency and accuracy of resource scheduling. Effective resource allocation is critical for ensuring the continuous operation of critical infrastructure, minimizing disaster-related losses, and expediting relief efforts. However, existing approaches often lack consideration for dynamic allocation and real-world constraints. The proposed framework aims to improve resource scheduling under these challenging conditions.

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Published
2024-12-04
DOI
https://doi.org/10.1109/ica63002.2024.00018
Primary Topic
Cloud Computing and Resource Management
Type
article
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article

BDI Agents Based Dynamic Resource Allocation in Emergency Scenarios

Jun Yan, Jennifer S. Shang, Fenghui Ren
Cloud Computing and Resource Management
article

BDI Agents Based Dynamic Resource Allocation in Emergency Scenarios

Jun Yan, Jennifer S. Shang, Fenghui Ren
article en

Abstract

This study proposes a dynamic resource scheduling framework based on a multi-agent system (MAS). The framework integrates the Belief-Desire-Intention model with fuzzy logic and time windows to enable efficient dynamic resource allocation. It is designed to address various uncertainties in emergency resource allocation, such as delays in data transmission and sudden changes in the external environment. These uncertainties impact the efficiency and accuracy of resource scheduling. Effective resource allocation is critical for ensuring the continuous operation of critical infrastructure, minimizing disaster-related losses, and expediting relief efforts. However, existing approaches often lack consideration for dynamic allocation and real-world constraints. The proposed framework aims to improve resource scheduling under these challenging conditions.

University of Wollongong (AU)
Openalex Percentile: Top 62%
Cloud Computing and Resource Management
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BDI Agents Based Dynamic Resource Allocation in Emergency Scenarios — Jun Yan, Jennifer S. Shang, et al. · (2024) | TGRS Research Map | TGRS