LLM Agents Shatter Classical BFT Bound via Confidence-Weighted Consensus
Confidence Probing-based Weighted BFT leverages LLM agents' inherent skepticism to exceed the classical $f < n/3$ fault tolerance limit, fundamentally enhancing consensus security.
Time-Exact Multi-Blockchains Ensure Predictable Decentralized Multi-Agent Systems
Leverages polynomial complexity and hierarchical architecture to guarantee predictable, time-exact transaction finality, enabling trustworthy AI coordination.
Deterministic Causal Structure Decouples Ledger Correctness from Ordering Policy
This theory introduces a Deterministic Causal Structure (DCS) where the ledger is a policy-agnostic DAG, resolving the entanglement of correctness and ordering.
Blockchain Framework Fosters Transparent, Incentive-Compatible LLM Multi-Agent Collaboration
A novel blockchain framework enables decentralized Large Language Model agents to collaborate transparently with aligned incentives, overcoming centralized coordination limitations.
AI Agents Enhance Blockchain Security and Usability through Novel Architectures
This research introduces a systematization of AI agents for blockchain, proposing a four-layer architecture that enables intelligent automation and addresses critical security and privacy challenges.
Coral Protocol Unveils V1 Remote Agents for Multi-Agent AI Deployment
Coral Protocol's v1 introduces a Solana-powered, composable framework for AI agents, streamlining multi-agent system development and fostering a monetized "Internet of Agents."
DLT-Anchored Identities and Micropayments Empower Autonomous Multi-Agent AI Economies
This research introduces a novel distributed ledger technology architecture that provides secure, verifiable identities and blockchain-agnostic micropayments for autonomous AI agents, enabling trusted multi-agent economic interactions.
Integrated Architecture Secures Multi-Agent Systems with Privacy and Scalability
This research introduces a novel architecture combining DIDs, ZKPs, Hyperledger Fabric, OAuth 2.0, and CQRS to forge a secure, scalable, and privacy-centric framework for decentralized multi-agent decision-making.
