Software Developer, Digital Artist, and Builder of Things That Learn

I build client-side autonomous entities, digital grimoires, and interactive simulations that run entirely in browser-based and device-native environments.

🌐 Experience My Active Projects: ardorlyceum.itch.io

An immersive narrative simulation that models human consciousness, memory, and reality as a command-line operating system.

• Interactive Terminal: Run BIOS of Being on Itch.io
• The Consciousness Operating System Manual: A 100-page privileged manual (DLC) featuring kernel decryption keys and archetype installation codes. Archived in the San Diego Central Library's permanent collection.
• Master Registry: Lyric Database: Database Uplink
• BIOS_OS: The Sonification Cycle: Listen to the 24 Tracks
• Keygentia AI Taxonomy Engine: keygentia.netlify.app

A sci-fi living illustration published on Steam. Not a game. A microscope interface you actually look through, finding patterns and shapes that reveal the lifeforms that live on the surface of your skin.

• Steam Store: Integument on Steam
• DLC Expansion: Integument - Database Gates

An experimental browser-based digital art piece exploring how an artificial entity learns and visualizes its own mind.

• Live App & Devlog: Run SUKOSHI on Itch.io

v7 - Self-Directed Capability Development

ARMINTA is a Python-based autonomous causal discovery agent running continuously on Linux. It does not passively monitor the OS. It actively intervenes, measures outcomes, and builds a grounded causal model of your specific hardware from scratch. Every edge in the model is earned through real actions and empirical observation.

Key v7 Features:

• Wish Pipeline (W1-W4) - self-directed capability development triggered during SELF_ASSESS. W1 detects causal dead zones and situation gaps in the learned world model. W2 searches for procurement candidates from existing system utilities and the action registry. W3 runs shadow staging for ~2000 steps with no execution - observe only, with routing validation gates. W4 grades over 5000 steps and returns WIN/TIE/LOSE verdicts. W4b generates implementation code from her own source via AST on WIN, backs up the current source, and appends staged actions for human review.
• Full v6 foundation retained: HobbyCore - voluntary external engagement layer. Fires during DREAM cycles when emotional state is receptive. Samples four probe domains (public network latency, local hardware sensors via sysfs, system load index, and solar/daylight context) using intensity-weighted domain interest.
• EarlyOOM Observation Node - earlyoom_ct as an observational-only SCM metric. All action -> earlyoom_ct causal edges are poison-listed at write time. The agent learns preconditions that precede OOM kills.
• Circadian Memory Look-Ahead - _check_circadian_memory() fires compact_memory during predicted idle lulls before historically high-RAM hours. Log prefix [CIRC-MEM].
• Full v5 foundation retained: PriorityShift (focus-aware dynamic process priority, RL-learned nice delta), SelfTuner + ActionProposer + SandboxRunner (self-expanding action space), zRAM-aware memory management, battery-aware action gating, and the complete v4 cognitive hierarchy (Temporal Causal Graph, DDQN CMC, MosaicCore, LexicalCore, WebLearner, SomaticConfidenceModel, etc.).

Live Stats (pushed directly from the running agent): Live Agent Dashboard

Full architecture, cognitive hierarchy (updated Mermaid diagram), version lineage, and detailed documentation are in the repo.

Status: Active development at v7.

• NoSight
• Drawmation

Maintainer: Jason German (mematron)