Drive, Intelligence, and Suffering

an affordance is an awareness of one’s environment with respect to goals that are currently driving behavior and the actions that are currently possible to perform. one recognizes affordances by predicting the effects of actions in the current environment and making judgements based on the desired trajectories corresponding to goals and the expected trajectories of …

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 …

Online Batch Learning

Overview online batch learning is an algorithm for unsupervised learning that mimics the process of batch learning entirely online. OBL enables continuous improvement while taking advantage of powerful techniques utilized in offline machine learning. the primary goal of OBL is to form a foundation on which to build intelligent agent architectures, whose ability to create …

Predictive Dual-Intelligence

PDI is an intelligent agent architecture and unsupervised learning algorithm for constructing models of an environment in real-time to be used for planning and decision-making by an intelligent agent. A PDI agent is embodied, meaning it exists within and as part of a larger environment, and adaptive, meaning it changes behavior in response to interactions …

An Intelligent Agent that Builds High-Level Models to Maximize Fitness

the following lays out a framework for an adaptive decision-making agent that constructs models of the world to behave intelligently and maximize its fitness. models and decisions models are structures that represent situational and behavioral patterns. actions that lead to changes in an environment are equivalent to state transitions or paths between differing scenarios. decision-making …

Mathematical Foundations of Knowledge

Overview As intelligent beings, we’re able to interpret constraints that effect our understanding of the spatial, temporal, social, political, and economic world that we inhabit. Our intuitive realization of boundaries, I argue, stems from the built-in neurological mechanism of classification and pattern recognition. In order to frame experiences in a meaningful way, there must be …

On Relational Knowledge Representation

Overview In order to effectively represent knowledge so that it may be utilized in future problem-solving, it is necessary to encode relational information beginning at the spatial-temporal dimension and working upward with increasing complexity, such that the relations at higher levels are constructed from those below, with the result being a theoretically infinite hierarchy of …

Adaptive Template Model of Intelligence

Click to see this project on GitHub 1. Introduction 1.1) Problem Overview Traditionally, template-matching algorithms have been used for things like digital image processing and visual pattern recognition. There are typically sets of small, two-dimensional filters that are moved across a gray-scale image in order to detect instances of low-level visual patterns. Pattern recognition via …

A Frame-Based Approach to the Nature of Knowledge

Slots and Types A slot is a data structure that holds a value within a particular domain at any given time. Slots represent abstract types and the values held at any given time represent instances of the types, where the domain is the set of known instances of the type. Each possible value is mutually …

Linguistic Development and Constructed Meaning

The following is an explanation of the various forms of information, as well their applications, within this system. Classes Data is passed through sensors and stored in an input vector, where local contrast is measured over space to extract feature vectors. Spatial patterns, called objects, are detected as relationships between features over space, while temporal …