James A. Anderson

Papers

Total Citations

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About

James A. Anderson is a researcher whose work bridges computer vision, robotics, and theoretical artificial intelligence. His most-cited paper, "A CAD-based computer vision system" (1998, 33 citations), reflects an early and sustained interest in integrating geometric modeling with visual perception—a foundational contribution to the field of CAD-driven robotic vision. However, Anderson is perhaps best known for his provocative and ambitious work on "Robot free will" (2002, 2 citations), which introduces the concept of the perspex machine—a theoretical framework that unifies projective geometry with Turing computation to create a supra-Turing machine. In this work, Anderson demonstrates two ways the perspex machine can unify symbolic and non-symbolic AI, including concrete geometric models that map perspexes onto neural networks. Though less cited, this paper represents a bold attempt to bridge computational theory, geometry, and consciousness, challenging conventional boundaries in AI. Anderson’s career reflects a rare combination of practical systems engineering and deep theoretical speculation, making him a distinctive voice in the ongoing dialogue between computation, perception, and machine autonomy.