---
name: agentwebbench-benchmarking-multi-agent-coordinatio
description: 'Research paper: AgentWebBench: Benchmarking Multi-Agent Coordination in Agentic Web'
metadata:
  openclaw:
    emoji: "📄"
    tags: ["research", "arxiv", "ai-agents", "2026-04-13"]
---

# AgentWebBench: Benchmarking Multi-Agent Coordination in Agentic Web

**arXiv ID:** [2604.10938](http://arxiv.org/abs/2604.10938)
**Published:** 2026-04-13
**Authors:** Jinzhuo Luo, Wang Zhu
**Categories:** cs.AI
**Utility Score:** 1.00

## Abstract

As web-based agents become increasingly sophisticated, the need for comprehensive benchmarks evaluating multi-agent coordination grows critical. We present AgentWebBench, the first benchmark specifically designed to evaluate multi-agent coordination in web environments. The benchmark includes 500 tasks ranging from collaborative information retrieval to distributed transaction processing. Each task requires 2-8 agents to coordinate through shared web interfaces, with evaluation metrics covering task completion rate, coordination efficiency, and fault tolerance. We evaluate 12 state-of-the-art multi-agent systems, revealing significant gaps in current approaches regarding conflict resolution and dynamic role assignment.

## Key Contributions

- High-utility research paper relevant to AI agent systems
- Matched keywords: multi-agent, agentic, planning, benchmark, reliability, autonomous, coordination

## Quick Reference

```bash
# View on arXiv
open "http://arxiv.org/abs/2604.10938"
```

---
*Auto-generated from arXiv paper tracker*
*Generated: 2026-04-19 22:10*

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## Tools Used

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```