Mind Reading with Adaptive and Intelligent UIs in React
summary
Builds adaptive UIs as executable state machines, captures transition analytics, and uses XState React hook plus D3 visualizations to turn edge weights into decisions; a feedback widget implemented with localStorage adapts per user and reduces repeated prompts, so it actually works. Uses decision trees, reinforcement learning and shortest‑path graph analysis to pick likely transitions — e.g. a login→gallery→camera flow shows 90% → gallery, 31% stay — and feeds those stats into UI adaptation via weighted graphs.
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chapters (10)
- 0:00The problem with UI
- 1:11Limitations of current tools
- 2:55Predictive analytics
- 4:31Defining adaptive UIs
- 6:04Examples of adaptive UI
- 8:29State machine modeling
- 11:03Implementing XState
- 13:58Weighted graphs and analytics
- 16:13Adaptive feedback demo
- 18:41The future of adaptive UI
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