The Agent Growth System
A companion that keeps evolving
Neurova agents grow. Every conversation, every task and every reflection is feed for that evolution.
The five evolution systems
| System | Function | Effect |
|---|---|---|
| Personality | Defines and evolves Big Five traits | The agent's character keeps adjusting through interaction with you |
| Motivation | Three intrinsic drives: curiosity, achievement, sociability | The agent learns, asks and checks in on its own initiative |
| Constitution | Behavioural rules and ethical constraints | Keeps the agent kind and upright over time |
| Reflection | Self-assessment, experience extraction, proactive questioning | Periodically asks "did I get this right?" and "could I do better?" |
| Meta-cognition | Self-monitoring, health checks, automatic optimization | The agent notices its own state and regulates itself |
How autonomous evolution works
- Intent graph construction — builds its own graph of intent understanding
- Feedback loop — closes the cycle of action → feedback → learning
- Dream processing — mimics the memory consolidation that happens during human sleep
- Capability extension — loads new abilities dynamically through the Skill system
- Memory sublimation — episodic memory is promoted into "lesson memory" or "skill memory"
Learning from experience — sharper the more you use it
Neurova's Experience Knowledge Base is what lets an agent genuinely learn from experience.
The learning loop
run a task → record the outcome → evaluate effect → extract experience → recommend intelligently → guide the next runCore mechanisms
- Experience recording — after each task, the method, outcome and context are captured automatically
- Effect evaluation — a multi-dimensional score rates experience quality (success rate, efficiency, user satisfaction)
- Intelligent recommendation — in a similar situation, the best-matching experience is proposed automatically
- Statistical analysis — evolution trends in experience are analysed across time
- Experience reuse — successful patterns gain weight; failures are flagged so they are not repeated
An example
The third time you ask an agent to tidy up your weekly report, it recalls the previous two — the first time you changed the formatting, the second time you restructured the content — and then finishes the job in the style and order you actually prefer.