The Power of Language, Ideological Conformity, and Consumer Skepticism

Reinforcement, a learning mechanism based on reward and punishment to sculpt the behavior of dogs, children, employees, etc., produces individuals that suppress behavior which is incorrect for a given context. Long-term, they conform to a set of rules dictating what is good within a given system. The desires or goals of the individuals converge to …

Unsupervised Hierarchical Feature Learning

Introduction and OverviewAn unsupervised hierarchical feature learning system is an unsupervised learning algorithm for extracting, recognizing, and predicting patterns online. It generates a hierarchy of patterns, each a composition of lower level features and learned through observations of streaming data. A pattern represents a state, and the lowest level state at any given time is …

A Predictive Unsupervised Neural Network w/ Spike-Timing Dependent Plasticity

A spike-timing dependent plasticity (STDP) network is a neural network that uses unsupervised learning to build a predictive model of the world. The learning algorithm that adjusts the weights in an STDP network is an online iterative algorithm that functions as a sort of expectation-maximization process. For each neuron in a network, the elapsed time …

Concurrent Learning Mechanisms to Boost Higher Intelligence

Different methods of learning are used to shape the many layers of the brain. This is not the way that standard applications of artificial intelligence seemingly modeled after the brain work, however. In almost all cases, the learning algorithms used today exhibit one or two basic processes that are capable of dealing with specific problems, …

A Path to Higher Intelligence through Mental Modeling

Describing states and events sufficiently is a problem overcome by all existing intelligent beings, and will be faced by all of those to come in the future. States, put simply, are collections of features arranged in a certain way that are used to describe potential configurations of the observable world. In biological systems, features originate …

Integrate-and-Fire Neural Networks for Intelligent Agents

View Code IAF Networks An Integrate-and-fire (IAF) network is a neural network that functions in real-time and resembles the functionality of a biological neural network more closely than traditional ANNs. IAF networks are well-suited for applications involving online environments because they are unsupervised and learn continuously. Specifically, these networks are designed for intelligent agent applications …

Foundations of Neural Systems

1. Introduction and Thesis Neural systems are complex adaptive systems that are designed around the functional and structural properties observed in the mind, particular the human mind. The organizational principles behind their designs are based on observations within biological, neurological and psychological frameworks. The goal of constructing such systems is to produce applicable machines that …