Reinforcement Learning

Reinforcement Learning is an area of machine learning inspired by behaviorist psychology, concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward.

Local Government Applications

Wikipedia notes that reinforcement learning is particularly well-suited to problems which include a long-term versus short-term reward trade-off. It has been applied successfully to various problems, including robot control, elevator scheduling, telecommunications, backgammon, checkers, and go.

This The Verge article notes that reinforcement learning has worked best for mastering games where:

  • the rules are finite,
  • there’s no element of luck,
  • there no hidden information,
  • researchers have access to a perfect simulation of the game.

The question is, are there any challenges facing local government that could be described thus?

Related Pages


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External Links & References

  1. Wikipedia
  2. Google Search
  3. What distinguishes reinforcement learning from deep learning? - Quora
  4. Deepmind's Go-Playing AI doesn't need human help to beat us any anymore - The Verge (October 2017)