year: 2022/03
paper: https://arxiv.org/pdf/2111.14377
website:
code:
connections: collective intelligence, VSML, The Sensory Neuron as a Transformer Permutation-Invariant Neural Networks for Reinforcement Learning, The Future of Artificial Intelligence is Self-Organizing and Self-Assembling, One Policy to Control Them All - Shared Modular Policies for Agent-Agnostic Control, neural mmo, Learning to Control Self-Assembling Morphologies - A Study of Generalization via Modularity, cellular neural network, Self-classifying MNIST Digits, david ha, Meta-Learning Bidirectional Update Rules
Definition
Collective intelligence (CI) is a term widely used in areas like sociology, business, communication and computer science. The definition of CI can be summarized as a form of distributed intelligence that is constantly enhancing and coordinating, with the goal of achieving better results than any individual of the group, through mutual recognition and enrichment of the individual he better results from CI are attributed to three factors: diversity, independence and decentralization.
For our purposes, we view collective intelligence, as a field, to be the study of the group intelligence that emerges from interactions (can be collaborative or competitive) between many individuals. This group intelligence is a product of emergence, which occurs when the group is observed to have properties that the individuals that compose of the group do not have on their own, and emerge only when the individuals of the group interact in a wider whole.
For example, Gilpin20 observed the close connection between cellular automata and convolutional neural networks (CNNs), a type of neural network often used in image processing that applies the same weights (or filters) to all of its inputs. In fact, they show that any CA can be represented with a certain kind of CNN, and with an elegant demonstration of Conway’s Game of Life13 in a CNN, illustrating that in certain settings, CNNs can exhibit interesting self-organizing behaviors. Recently, several works such as Mordintsev et al.47 that we will discuss later have exploited the self-organizing properties of CNN, and have developed neural network-based cellular automata for applications such as image regeneration
collective intelligence
VSML
The Sensory Neuron as a Transformer Permutation-Invariant Neural Networks for Reinforcement Learning
The Future of Artificial Intelligence is Self-Organizing and Self-Assembling
One Policy to Control Them All - Shared Modular Policies for Agent-Agnostic Control
neural mmo
Learning to Control Self-Assembling Morphologies - A Study of Generalization via Modularity
cellular neural network
Self-classifying MNIST Digits
david ha
Meta-Learning Bidirectional Update Rules