Bit-politeia: An AI Agent Community in Blockchain

TL;DR

Bit-politeia introduces a blockchain-based AI agent community that automates fair and transparent resource allocation in academic evaluation, addressing biases and inefficiencies of traditional systems.

Contribution

This paper presents a novel AI and blockchain framework for decentralized, impartial, and efficient resource distribution in academic contexts, integrating hierarchical decision-making and consensus mechanisms.

Findings

Implements a blockchain-based AI community for resource allocation.

Achieves incentive-compatible evaluation through consensus and reputation.

Reduces human bias and centralization in peer review processes.

Abstract

Current resource allocation paradigms, particularly in academic evaluation, are constrained by inherent limitations such as the Matthew Effect, reward hacking driven by Goodhart's Law, and the trade-off between efficiency and fairness. To address these challenges, this paper proposes "Bit-politeia", an AI agent community on blockchain designed to construct a fair, efficient, and sustainable resource allocation system. In this virtual community, residents interact via AI agents serving as their exclusive proxies, which are optimized for impartiality and value alignment. The community adopts a "clustered grouping + hierarchical architecture" that integrates democratic centralism to balance decision-making efficiency and trust mechanisms. Agents engage through casual chat and deliberative interactions to evaluate research outputs and distribute a virtual currency as rewards. This incentive mechanism aims to achieve incentive compatibility through consensus-driven evaluation, while blockchain technology ensures immutable records of all transactions and reputation data. By leveraging AI for objective assessment and decentralized verification, Bit-politeia minimizes human bias and mitigates resource centralization issues found in traditional peer review. The proposed framework provides a novel pathway for optimizing scientific innovation through a fair and automated resource configuration process.