SEED is a structural encoding framework using typed actor-flow graphs to describe, evaluate novelty of, and generate experimental designs for AI-enabled science under feasibility and governance constraints.
AI Agents as Team Members: Effects on Satisfaction, Conflict, Trustworthiness, and Willingness to Work With
4 Pith papers cite this work. Polarity classification is still indexing.
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Ledger-state stigmergy maps biological indirect coordination to blockchain ledgers via a state-transition formalism and three base patterns for on-chain agent coordination.
AUTOBUS is a neuro-symbolic architecture that uses AI agents to generate executable logic programs from business instructions and knowledge graphs for end-to-end process automation with human supervision.