MC-EvoBench: Auditing Experience-Driven Self-Improvement in Minecraft Agents
A central challenge in embodied recursive self-improvement is enabling agents to convert interaction history into capabilities that persist beyond one world and transfer to later tasks. A saved memory or successful final action does not by itself establish that a reusable capability was acquired; evaluation must separate capability change from carried-over resources, unequal source exposure, and early execution failures. We construct MC-EvoBench as a controlled Minecraft benchmark with a fixed catalog of 19 registered evolution chains, including 12 primary evaluation chains and seven calibration or probe chains, together with three graph-aligned paired probe families for transfer. The ben...
| Authors | Jingwei Song, Zhisheng Chen, Bingfan Zeng et al. |
|---|---|
| Primary category | cs.RO |
| Published | 9 October 2026 |
| Last updated at source | 9 October 2026 |
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