An Active Inference Model of Collective Intelligence

Active Inference for Collective Classification

Labeling nodes in a network is an important problem that has seen a growing interest. A number of methods that exploit both local and relational information have been developed for this task. Acquiring the labels for a few nodes at inference time can greatly improve the accuracy, however the question of figuring out which node labels to acquire is challenging. Previous approaches have been base...

Human collective intelligence as distributed Bayesian inference

Collective intelligence is believed to underly the remarkable success of human society. The formation of accurate shared beliefs is one of the key components of human collective intelligence. How are accurate shared beliefs formed in groups of fallible individuals? Answering this question requires a multiscale analysis. We must understand both the individual decision mechanisms people use, and ...

Collective Intelligence: An Overview

Collective Opinion Spam Detection using Active Inference

Opinion spam has become a widespread problem in the online review world, where paid or biased reviewers write fake reviews to elevate or relegate a product (or business) to mislead the consumers for profit or fame. In recent years, opinion spam detection has attracted a lot of attention from both the business and research communities. However, the problem still remains challenging as human labe...

An Introduction to Collective Intelligence

This paper surveys the emerging science of how to design a “COllective INtelligence” (COIN). A COIN is a large multi-agent system where: i) There is little to no centralized communication or control. ii) There is a provided world utility function that rates the possible histories of the full system. In particular, we are interested in COINs in which each agent runs a reinforcement learning (RL)...