The framework models a multi-step workflow as a sequential auction within a Markov decision process.
Imperfect competition can sustain decentralized markets for multi-step LLM tasks
Sequential auctions let heterogeneous agents coordinate, earn positive margins and preserve task performance without a central orchestrator.
Big Tech
Ian Gemp · Shubhendu Trivedi · Adam Fisch · Fantine Huot · Michael Kaisers · Mirella Lapata · +4 more
Google DeepMind · Google Research · University of Waterloo
Research Digest··3 min read
Thread:LLM Agent Markets
The authors organize specialized LLM agents into a market where each agent buys an intermediate task state, transforms it and auctions the result onward.
Why this paper
From Google DeepMind and 2 others
In one line
Imperfect competition in sequential LLM auctions preserves agent profits and task accuracy, while perfect cloning removes incentives and monopsony collapses value propagation.
What we could check
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