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[P] Implemented ACT-R cognitive decay and hyperdimensional computing for AI agent memory (open source)
Built a memory server for AI agents (MCP protocol) and implemented two cognitive science techniques in v7.5 I wanted to share. ACT-R Cognitive Decay Memory nodes fade using the base-level activation formula: B_i = ln(Sum t_j -d ) Old, rarely-accessed memories lose salience. Frequently-accessed ones stay vivid. This keeps agent context clean without manual pruning - only "warm" memories surface at retrieval time. Hyperdimensional Computing (HDC) Routing Agent state is encoded as XOR of three 768-dim binary hypervectors: state x role x action. Routing uses Hamming distance rather than cosine similarity - works surprisingly well for sparse, structured agent state. Background Edge Synthesis A background process autonomously discovers and links semantically similar memory nodes. The graph selfo
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