A feedback loop uses the consequences of an action to guide what happens next. Signals such as rewards, penalties, or changes in body data can encourage different choices over time. section 1.30 section 10.2
Adjusting a workout
Wearables track signals such as heart-rate variability, blood oxygen, and sleep. An AI model can use those signals to adjust workout intensity or suggest recovery when it detects fatigue. section 1.30
Learning through rewards
A dog that receives a treat after sitting is more likely to repeat the action. In reinforcement learning, rewards encourage actions and penalties discourage them; choices are judged by their longer-term consequences, not only their immediate payoff. section 10.2 section 10.2
Figure 1.10 Using sensors and AI to guide fitness and health
The figure illustrates how sensor data and AI can guide fitness and health decisions. section 1.30
