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README.md

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 ---
 license: mit
+tags:
+- multi-agent-path-finding
+- mapf
+- multi-agent-reinforcement-learning
+- reinforcement-learning
+- robotics
+- decentralized-planning
+- pytorch
 ---
+
+# SYLPH: Social Behavior as a Key to Learning-Based Multi-Agent Pathfinding Dilemmas
+
+This repository provides the pretrained model for **SYLPH**, introduced in:
+
+> **Social Behavior as a Key to Learning-Based Multi-Agent Pathfinding Dilemmas**
+
+SYLPH is a learning-based Multi-Agent Path Finding (MAPF) framework that explicitly models social behaviors among agents to improve decentralized coordination in challenging multi-agent interactions.
+
+The pretrained checkpoint provided here corresponds to the policy used for evaluation in the paper.
+
+## Model Overview
+
+Multi-Agent Path Finding requires multiple agents to navigate toward their individual goals while avoiding collisions with obstacles and other agents.
+
+Learning-based decentralized MAPF methods can struggle in challenging interaction scenarios, particularly when agents encounter coordination dilemmas caused by competing paths and limited shared space.
+
+SYLPH introduces social behavior into the learned policy to facilitate coordination among agents and improve their ability to resolve these interactions.
+
+### Key Features
+
+- Decentralized multi-agent path planning
+- Learning-based coordination
+- Socially-aware agent behavior
+- Multi-agent reinforcement learning
+- Designed for challenging MAPF interaction scenarios
+- Shared policy across agents
+
+## Model Files
+
+The repository contains the pretrained SYLPH policy checkpoint:
+
+```text
+net_checkpoint.pkl