This is my favourite example of reinforcement learning.
Let me explain...
1. Environment: The assault course.
2. Agents: The dogs.
3. States: Position, obstacles, path to the prize.
4. Actions: Jumping, running, dodging.
5. Rewards: Overcoming obstacles, winning the prize.
6. Policy: Strategy for actions (e.g., jump when facing a hurdle).
7. Learning from Mistakes: Trying new approaches after failure.
8. Observation and Adaptation: Learning strategies by watching other dogs.
9. Optimal Strategy: Finding the best way to complete the course.
10. Generalisation: Applying learned skills to new challenges.
They gradually find the most effective strategies to achieve their goal—a tasty treat.
My takeaway:
I think this is a wonderful example that captures the core principles of reinforcement learning, how persistence and adaptation lead to success.
It's also a great reminder of how AI can mimic natural learning processes.
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