What problem does it solve?
Allocates tasks across autonomous agents in a decentralized setting using bid-based negotiation so that work is assigned efficiently, deterministically, and with explicit recovery when agents fail or information is partial. It prevents race conditions, duplicate work, and coordination breakdowns by combining contract bidding with epistemic checks that ensure agents "know enough" before committing to tasks.
Core Features & Use Cases
- Contract-Net Bidding: Structured announce-call-bid-award cycles to let agents bid for tasks based on local cost, capability, and availability.
- Epistemic Preconditions & Verification: Model-checking style guards that verify an agent has the required knowledge/observations before accepting a contract.
- Failure Recovery & Salvage: Procedures for reclaiming and redistributing unfinished work from crashed or unresponsive agents.
- Use Cases: Distributed robotics task distribution, decentralized microservice job scheduling, peer-to-peer crowdsourcing marketplaces where atomic assignment and knowledge guarantees are required.
Quick Start
Run a contract-net auction among available agents to assign the "process_orders" task while prioritizing low latency, capability fit, and resilience to agent failure.
