Twelve Theories of Consciousness Reconsidered. An Adversarial Multilayer Analysis Through Reality Architecture and Perception Mechanism Theory

This paper revisits twelve major approaches to consciousness through the evolving framework of Reality Architecture and Perception Mechanism Theory (RA/PMT). Rather than treating Materialism, Dualism, Panpsychism, Integrated Information Theory, Global Neuronal Workspace Theory, quantum approaches, Higher-Order Thought, Predictive Processing, Attention Schema Theory, Neural Correlates of Consciousness, Emergentism, and Computational Models as competing attempts to answer a single question, the paper examines whether they may address different explanatory levels of consciousness. This reconstruction substantially revises an earlier comparison. Subsequent development of RA/PMT, together with architectural lessons arising from the development of Salomon-Prime, motivated a more rigorous adversarial methodology. The revised analysis distinguishes potentiality, representation, constraint, Intent, intention, agency, selection, physical realization, perceptual construction, observation, and experiential feedback, while also identifying unresolved questions within RA/PMT itself. Importantly, RA/PMT is not presented here as an established solution to the problem of consciousness. It is evaluated under the same critical standards applied to the twelve theories. The paper asks what each framework explains, what remains unresolved, what evidence would discriminate among competing explanations, and what findings could require RA/PMT itself to be modified or rejected. The central proposal is that theories of consciousness may occupy partially overlapping explanatory coordinates rather than constituting mutually exclusive accounts. RA/PMT is therefore presented as a candidate multilayer architecture for mapping relations among these explanatory levels and for developing testable, potentially falsifiable distinctions. The paper concludes with an explicitly open research position: RA/PMT should continue to evolve in response to empirical evidence, competing explanations, conceptual criticism, and adversarial testing rather than being protected from evidence that might challenge its assumptions. This version also notes the newly proposed concept of qualiaphobic AI as a timely example of why distinguishing functional capability, architectural properties, and consciousness has become increasingly important.