Resource utilization estimation and allocation for multi-agent computational systems

Abstract

Systems, methods, and devices for facilitating computational resource access by artificial intelligence (AI) agents through token-based allocation and multi-agent workflow optimization. The system generates tokens corresponding to computational resources including processing power, memory, storage, and bandwidth. AI agents submit resource requests with priority tokens, creating queues ordered by priority token quantity. Higher-priority bids receive preferential positions. The system transfers resource tokens to agents based on queue order, enabling resource access through token exchange. The system can receive user prompts indicating computational objectives and determines multiple AI agentic approaches comprising AI model sequences. After evaluating approaches against operational policies, the system generates resource utilization and performance estimates, executing a preferred approach balancing efficiency with output quality. All transactions, including participating agents, token transfers, selected agentic approaches, and estimates, are recorded on a distributed ledger for transparency.