Deluded_v0.1_default.zip

provides a baseline for understanding how software can "deceive" itself. Future iterations (v0.2 and beyond) will focus on "Intervention Protocols"—methods to break these self-reinforcing loops and restore objective processing. Suggested Tags / Keywords:

The v0.1 release focuses on the . We utilize three primary modules: Deluded_v0.1_default.zip

We introduce , an experimental framework designed to analyze "machine delusion"—the phenomenon where deep learning models develop reinforced, self-validating feedback loops. Unlike standard hallucinations, which are transient, these delusions represent persistent structural biases within the model's latent space. This paper outlines the "default" configuration of the Deluded v0.1 engine, detailing its ability to simulate confirmation bias and overconfidence in predictive analytics. 2. Introduction provides a baseline for understanding how software can

A recursive loop that prioritizes internal model weights over new sensory input. We utilize three primary modules: We introduce ,

#MachineLearning #CognitiveBias #Cybersecurity #RecursiveAI #DigitalPsychology zip configuration or the ethical implications?

Paper Title: Project Deluded: Quantifying Cognitive Distortions in Recursive Neural Architectures (v0.1) 1. Abstract