Project
Reverse Dependencies for legion-gaia
The projects listed here declare legion-gaia as a runtime or development dependency
0.0
Autobiographical narrative identity for LegionIO — the agent constructs and maintains a life narrative of who it is, what it has done, and what it values, based on Dan McAdams narrative identity theory
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Narrative reasoning engine for brain-modeled agentic AI — story structure, causal chains, arc progression
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Models autonoetic consciousness — maintains an autobiographical narrative of episodes, narrative threads, and an evolving self-concept that emerges from the pattern of lived experience.
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0.0
Cognitive narrative stream for brain-modeled agentic AI
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Brain rhythm coordination for LegionIO — theta, alpha, beta, gamma oscillations synchronizing distributed cognitive processing
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Neuromodulatory system modeling dopamine, serotonin, norepinephrine, and acetylcholine pathways for brain-modeled agentic AI
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Helmholtz unconscious inference engine: Bayesian perceptual hypothesis selection, rivalry detection, and top-down prior adaptation for brain-modeled agentic AI
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Big Five personality model emerging from accumulated cognitive behavior patterns
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Systematic multi-viewpoint analysis engine for brain-modeled agentic AI — cycles through stakeholder, ethical, temporal, and other interpretive frames to generate richer situational understanding
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Phenomenal binding engine for LegionIO — unifies disparate cognitive streams into coherent conscious experience
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Models the prefrontal cortex planning function: plan trees, progress tracking, contingencies, re-planning
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Gricean cooperative maxims and conversational implicature engine for brain-modeled agentic AI
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Forward-model prediction engine (4 reasoning modes) for brain-modeled agentic AI
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Karl Friston's Free Energy Principle / Predictive Processing framework for brain-modeled agentic AI
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Andy Clark's Predictive Processing / Active Inference for brain-modeled agentic AI: generative models, precision-weighting, active inference, and free energy minimization
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Learns and models preferences from choices and feedback for brain-modeled agentic AI
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Models spreading activation in semantic networks — stimuli prime related concepts, lowering their activation threshold and speeding future access.
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0.0
Anderson's ACT-R production rules — skill acquisition from declarative to autonomous for brain-modeled agentic AI
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Future-oriented mental simulation: imagines future scenarios, predicts their emotional impact, tracks impact bias and focalism corrections, and calibrates forecast accuracy over time. Based on Gilbert & Wilson affective forecasting research.
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Prospective memory engine: manages intentions, monitors trigger conditions, and executes when conditions are met
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