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Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Chang Liu

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2 papers indexed here

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Book Open access Aug 2026

Toward Efficient LLM Agents for Emulator-Based Network Experiment Automation

A Network Experimentation Harness for emulator-backed network experiments, helping LLM agents operate across these stateful workflows by pairing a semantic action interface with reusable experimentation skills to handle sequencing, timing, and verification that a careful experimenter would perform by hand.

Chenguang Du, Chang Liu, Lei Zhang et al. · 0 citations
Preprint Aug 2026

NetConfArena: An Executable Benchmark for LLM Agents in Closed-Loop Network Configuration

NetConfArena is presented, an executable benchmark for evaluating LLM agents in closed-loop network configuration, and its findings suggest two future directions: using validated trajectories as supervision signals to improve foundation models, and designing harness mechanisms that make agent execution more reliable and accountable.

Chang Liu, Xiaohui Xie, Xinyi Chen et al. · 0 citations