An Analysis of Contemporary Approaches to Artificial General Intelligence
This thesis examines the current state of Artificial General Intelligence (AGI) research through the lens of converging paradigms. We analyze symbolic reasoning, neural networks, embodied cognition, and quantum computing approaches, proposing a unified framework that addresses the fundamental challenges of consciousness, learning, and adaptation in artificial systems. Our research suggests that AGI emergence requires not incremental improvements within single paradigms, but rather the orchestrated integration of multiple computational frameworks.