Beyond Predefined Learning Objects: A Thinking-Learning Interaction Model for Up-to-Date Autonomous Robot Learning

In three linesThinking-learning interaction model for autonomous robots in changing environments. Thinking guides learning (change identification, evidence selection, planning), learning improves thinking (knowledge updates, action strategies). Results: recognition accuracy 0.419→0.845, action length 13.0→4.0, evidence selection rate 0.272→0.965.

Summary generated by Claude — human-verified