The Reflexive Integrated Information Unit: A Differentiable Primitive for Artificial Consciousness
- URL: http://arxiv.org/abs/2506.13825v1
- Date: Sun, 15 Jun 2025 14:07:59 GMT
- Title: The Reflexive Integrated Information Unit: A Differentiable Primitive for Artificial Consciousness
- Abstract summary: We introduce the Reflexive Integrated Information Unit (RIIU), a recurrent cell that augments its hidden state $h$ with two additional vectors.<n>A sliding-window covariance and a differentiable Auto-$Phi$ surrogate let each RIIU maximize local information integration online.<n>In an eight-way Grid-world, a four-layer RIIU agent restores $>90%$ reward within 13 steps after actuator failure, twice as fast as a parameter-matched GRU.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Research on artificial consciousness lacks the equivalent of the perceptron: a small, trainable module that can be copied, benchmarked, and iteratively improved. We introduce the Reflexive Integrated Information Unit (RIIU), a recurrent cell that augments its hidden state $h$ with two additional vectors: (i) a meta-state $\mu$ that records the cell's own causal footprint, and (ii) a broadcast buffer $B$ that exposes that footprint to the rest of the network. A sliding-window covariance and a differentiable Auto-$\Phi$ surrogate let each RIIU maximize local information integration online. We prove that RIIUs (1) are end-to-end differentiable, (2) compose additively, and (3) perform $\Phi$-monotone plasticity under gradient ascent. In an eight-way Grid-world, a four-layer RIIU agent restores $>90\%$ reward within 13 steps after actuator failure, twice as fast as a parameter-matched GRU, while maintaining a non-zero Auto-$\Phi$ signal. By shrinking "consciousness-like" computation down to unit scale, RIIUs turn a philosophical debate into an empirical mathematical problem.
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