Self-Evolving
Agent
Self-learning · self-optimizing · self-iterating · agent lifecycle
Inspired by Generative Agents, our agents keep learning during idle hours — consolidating experience, evolving personality, and forming a genuine growth-capable intelligence.
Concurrent routing+Decomposition+Idle-time growth
Three layers work in concert — giving the multi-agent system stronger complex-task handling, long-term memory, and self-evolution.
Three upgrade directions
Concurrent routing upgrade
Dynamic routing + parallel scheduling + co-acceleration. Complex requests are dispatched to the most capable agent by competence, eliminating single-point bottlenecks and lifting throughput by orders of magnitude.
Decomposition enhancement
Goal understanding + sub-task division + co-execution. Complex tasks are no longer a fog — they are precisely broken into executable, traceable, rollback-friendly sub-units.
Continual idle growth
Idle no longer means standby. Agents autonomously consolidate memory, reflect on experience, evolve capability and personality — a true lifecycle of intelligence.
Agent lifecycle · Observe-Think-Act-Learn
Sense, understand, remember, decide, act, feed back and learn form a complete loop. Every interaction becomes the foundation of a better next one.
Continuously perceives user behavior, environment state, sensor data — builds a live situational picture.
Multi-step reasoning across memory, persona and goals to plan the optimal action path.
Invokes tools, drives hardware, generates replies — turns decisions into real-world actions.
Feeds every interaction back into the memory stack and persona layer for continual calibration.
Idle hours: autonomously consolidates experience, forms self-reflection, tunes persona and strategy.
Continuously perceives user behavior, environment state, sensor data — builds a live situational picture.
Multi-step reasoning across memory, persona and goals to plan the optimal action path.
Invokes tools, drives hardware, generates replies — turns decisions into real-world actions.
Feeds every interaction back into the memory stack and persona layer for continual calibration.
Idle hours: autonomously consolidates experience, forms self-reflection, tunes persona and strategy.