This is the code repository for the paper "Graph Attention-Guided Search for Dense Multi-Agent Pathfinding" introducing LaGAT. LaGAT combines a neural policy heuristic, an enhanced MAGAT+ model, with ...

The assembly line upended manufacturing last century—could teams of agents do the same for white-collar work? When people say AI will speed up drug development or fear that it will bring about mass ...

We just can’t seem to help ourselves. Our current infatuation with multi-agent systems risks mistaking a useful pattern for an inevitable future, just as we once did with microservices. Remember those ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. As the CTO of an AI-native email management startup, I've spent the past year building multi ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. In this eMag, we try to establish agentic AI ...

In this section, we present fundamental definitions of multi-agent pathfinding. Since our method is dimensionindependent, the provided definitions apply to any-dimensional grid space CN .

Abstract: Multi-Agent Path Finding (MAPF) has been widely studied in recent years. However, most existing MAPF algorithms assume that an agent occupies only a single cell in a grid-based map. This ...

Abstract: This study informs the design of future multi-agent pathfinding (MAPF) and multi-robot motion planning (MRMP) algorithms by guiding choices based on constraint classification for ...

This repository collects reference implementations for training and evaluating reinforcement learning agents on multi-agent pathfinding problems. The environments explicitly support deadlocks so that ...

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