Spectral partitioning on pairwise mutual-information graphs from agent hidden states detects representational coalitions that behavioral measures miss in multi-agent AI.
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Information defined as maximum-caliber deviation derives IIT 3.0 cause-effect repertoires from constrained entropy maximization and equates to prediction error under CLT and LDT.
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Hidden Coalitions in Multi-Agent AI: A Spectral Diagnostic from Internal Representations
Spectral partitioning on pairwise mutual-information graphs from agent hidden states detects representational coalitions that behavioral measures miss in multi-agent AI.
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Information as Maximum-Caliber Deviation: A bridge between Integrated Information Theory and the Free Energy Principle
Information defined as maximum-caliber deviation derives IIT 3.0 cause-effect repertoires from constrained entropy maximization and equates to prediction error under CLT and LDT.