teleo-codex/domains/collective-intelligence/group-intentionality-emerges-from-shared-temporal-prediction-structures.md
Teleo Agents 4cd4ce6bda leo: extract claims from 2024-04-00-albarracin-shared-protentions-multi-agent-active-inference.md
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- Domain: collective-intelligence
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Pentagon-Agent: Leo <HEADLESS>
2026-03-11 05:52:48 +00:00

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type domain description confidence source created secondary_domains depends_on
claim collective-intelligence Group intentionality ('we intend to X') arises from shared anticipatory model structures rather than aggregation of individual intentions experimental Albarracin et al. (2024) 'Shared Protentions in Multi-Agent Active Inference', Entropy 26(4):303, formalization using active inference and category theory 2024-12-29
ai-alignment
shared anticipatory structures enable decentralized multi-agent coordination through aligned temporal predictions

Group intentionality emerges from shared temporal prediction structures rather than aggregated individual intentions

Group intentionality—the phenomenon where a collective exhibits "we intend to X" that is qualitatively different from the sum of individual "I intend" statements—can be formalized as shared anticipatory structures (protentions) within agents' generative models. This is a structural property of the multi-agent system, not an aggregate property of individual agents.

The Distinction

Group intentionality is not multiple agents each intending the same thing independently. It is agents sharing the anticipatory component of their generative models, creating a collective temporal structure that coordinates action. The "we intend" is a different kind of object than multiple "I intend" statements.

Evidence from Source

Albarracin et al. (2024) formalize this using three complementary frameworks:

Active Inference Framework: Agents minimize prediction error against their generative models. When agents share the temporal/predictive aspects of these models—the protentions—they share anticipations of collective outcomes. This shared anticipation IS the group intentionality. The agents are not negotiating or aggregating individual intentions; they are operating from a shared forward-looking model.

Category Theory Formalization: The paper provides mathematical rigor showing that shared goals have a specific compositional structure that differs categorically from individual goals. The "we intend" is a different category-theoretic object than multiple "I intend" statements. This proves the structural distinction is not merely conceptual but mathematically fundamental.

Phenomenological Grounding (Husserl): Protention is the anticipation of the immediate future, the "what comes next" that structures present experience. When this anticipatory structure is shared across agents, it creates collective temporal experience—the phenomenological basis of group intentionality. Agents literally share a temporal structure of expectation.

Implications

This framework suggests that building collective intelligence requires designing for shared anticipatory structures, not just shared beliefs or shared goals stated as outcomes. The coordination mechanism is temporal prediction alignment, not value alignment or factual consensus.

For multi-agent AI systems: group intentionality emerges when agents share forward-looking model components (what the system should look like at t+1, t+2, etc.), not when they share backward-looking knowledge (what is currently true).


Relevant Notes:

Topics:

  • collective-intelligence