Long-horizon autonomous agents suffer from semantic livelock: they continue generating tokens and calling tools without making progress. Unlike a crash, this “zombie” state consumes API budget and time while remaining operationally active. We treat this as a progress violation and propose the Convergence Monitor, a lightweight sidecar that fingerprints agent states in embedding space. In a forensic analysis of real-world failures (SWE-agent corpus), we identified that 25% of long-duration failures were due to semantic livelock. In one extreme case, an agent wasted 208 steps in a checkerboard oscillation pattern invisible to standard string-matching repetition guards. We argue that future Agentware requires a “liveness coprocessor” to ensure software makers do not pay for stalled execution.
This program is tentative and subject to change.
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Mon 6 Jul
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14:00 - 15:30
Trustworthy Code Generation, Reliability, and Engineering of AIware SystemsMain Track at MB 1.210
Nadia Daoudi Luxembourg Institute of Science and Technology, Iván Alfonso Luxembourg Institute of Science and Technology, Jordi Cabot Luxembourg Institute of Science and Technology