AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
This work introduces Pivot-and-Station Multi-Agent Path Finding (PS-MAPF), a MAPF variant in which a subset of tasked agents must each visit one of a set of interchangeable pivots before the entire fleet terminates at anonymous stations, one agent per station.
The method combines hierarchical environment modeling based on Finite Time-Expanded Network with an Event-Driven Predictive Control strategy, enabling each AGV to independently compute congestion-aware and conflict-free paths based on locally solved optimization problems.
The coordination of Automated Guided Vehicles (AGVs) in high-density industrial environments represents a critical challenge within Logistics 4.0, as traditional traffic management methods often lead to inefficiencies caused by negotiation-based priority assignment. To overcome the resulting limitations, this paper pre...
The Colored Traveling Salesman Problem (CTSP) is a seminal generalization of the Multiple TSP, where colors represent the heterogeneity of salesmen and their city visits. This work presents a time-critical extension, termed the Time-Critical CTSP (T-CTSP). By emphasizing the timing of visits, T-CTSP explicitly captures...
This study sets out to build an intelligent agent that plans vehicle routes and handles three-dimensional cargo loading at the same time and suggests that tying routing and loading together in a closed-loop setup makes plans easier to carry out.
We present a tractable approach to grid-based multi-agent path planning for inspection tasks that minimizes task completion time. We require all agents to collectively inspect all targets while (i) maintaining a user-defined separation distance, (ii) returning to charging stations as needed, and (iii) avoiding obstacle...
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