MULTI-AGENT ARTIFICIAL INTELLIGENCE SYSTEMS FOR COORDINATED TASK SCHEDULING IN COMPLEX CONSTRUCTION PROJECTS

Kimberly Calvo William

MULTI-AGENT ARTIFICIAL INTELLIGENCE SYSTEMS FOR COORDINATED TASK SCHEDULING IN COMPLEX CONSTRUCTION PROJECTS

Authors

Kimberly Calvo William

AI-Based Project Optimization Engineer, France.

Keywords:

Multi-Agent Systems, Task Scheduling, Artificial Intelligence, Construction Management, Coordination, Project Optimization

Synopsis

The complexity and scale of modern construction projects demand dynamic, real-time scheduling systems capable of handling diverse interdependencies across tasks, resources, and stakeholders. This paper proposes the application of Multi-Agent Artificial Intelligence (MAAI) systems to manage coordinated task scheduling in construction environments. Through a review of key literature, analysis of agent-based models, and exploration of AI integration, we demonstrate how MAAI enhances efficiency, conflict resolution, and adaptability. Simulation results highlight the capacity of agent-based systems to outperform traditional methods under uncertainty and changing project conditions.

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