Fundamentals of AI Revision

Edit Answers
12345678910111213141516
Across
  1. 3. games where one person's gain is equivalent to another person's loss
  2. 7. information received about the current state in a partially observable environment
  3. 9. partially observable Markov Decision process also known as
  4. 10. optimization technique applied to minimax algorithm to make system more efficient
  5. 12. Represent the elements of the problem that need to be assigned values in CSP
  6. 15. Decision-makers (agents) that interact in the system
  7. 16. "Try it, and if it fails, go back and try something else"
Down
  1. 1. "Don't consider what’s already known to fail.“
  2. 2. The set of possible values for each variable in constraint satisfaction problem
  3. 4. immediate gains from taking actions in a partially observable environment
  4. 5. Restrictions on the values that variables can take in CSP
  5. 6. games where Agents only have access to a subset of the total information available in the game
  6. 8. A function that evaluates the quality of an assignment in CSP
  7. 11. simulation generates a large number of random inputs based on the defined distributions and calculates the outcome of the system
  8. 13. probability of moving between states in a partially observable environment
  9. 14. Possible configuration of the environment in partially observable environment