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Winning concurrent reachability games requires doubly-exponential patience

Explore the intricacies of concurrent reachability games and winning strategies. Follow the rules of player interactions and delve into probabilistic strategies for optimal gameplay. Uncover algorithmic consequences and open problems in this challenging gaming landscape.

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Winning concurrent reachability games requires doubly-exponential patience

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  1. Winning concurrent reachability games requires doubly-exponential patience Michal Koucký IM ASCR, Prague Kristoffer Arnsfelt Hansen,Peter Bro Miltersen Aarhus U., Denmark

  2. W • Player 1 chooses A{t,h} • Player 2 chooses B{t,h} • If • A = B then move one level up, • A  B = t then move to 1st level, • A  B = h then Player 1 loses. 7 Example 6 Entrance fee: $15 Win: $20 5 4 3 2 1

  3. Entrance fee: $15 Win: $20 Observation: To break even, you need at least ¾ probability to win. Good news: you can win with probability arbitrary close to 1. Bad news: the expected time to win the game with probability at least ¾ is 1025 years (one move per day). … the age of universe: 1011 years

  4. … … Concurrent reachability games [de Alfaro, Henzinger, Kupferman ’98, Everett ’57] Two players play on a graph of states. At each step they simultaneously (independently) pick one of possible actions each and based on a transition table move to the next state. …

  5. Goals: Player 1 wants to reach a specific state or states. Player 2 wants to prevent Player 1 from reaching these states. Strategy of a player: • Memory-less (non-adaptive) – π : states  actions. • Adaptive– π : history  actions. Probabilistic strategy: π gives a probability distribution of possible actions.  Patience of a memory-less strategy π = 1/min non-zero prob. in π … [Everett ’57]

  6. Winning starting states: • Sure – Player 1 has a winning strategy that never fails. • Almost-Sure – Player 1 has a randomized strategy that reaches goal with probability 1. • Limit-Sure – For every  > 0, Player 1 has a strategy that reaches goal with probability at least 1 –  .

  7. P • Player 1 chooses A{t,h} • Player 2 chooses B{t,h} • If • A = B then move one level up, • A  B = t then move to 1st level, • A  B = h then move to state H. n Purgatoryn n-1 … H 3 2 1

  8. Our results Thm:1) For every 0<  < ½ , any -optimal strategy of Player 1 in Purgatoryn is of patience > 1/2n-2 . 2) For every l < n/2 , any (1 – 2-l )-optimal strategy of Player 1 in Purgatoryn is of patience > 22n-l-2. Thm:For every 0<  < ½ and every concurrent reachability game with m>61 actions in total, both players have -optimal strategies with patience < 1/242m.

  9. Thm:1) For every 0<  <’, if every -optimal strategy of Player 1 is of patience > t then the expected time to win the game by any ’-optimal strategy of Player 1 can be forced to be Ω( t ).  patience ~ expected time to win • All the results essentially hold also for adaptive strategies Recall: the expected time to win Purgatory7 with probability at least ¾ is 1025 years (one move per day).

  10. Algorithmic consequences Three algorithmic questions: • What are *-SURE states? PTIME [dAHK] • What are the winning probabilities of different states?  PSPACE [EY] • What is the (-)optimal strategy?  EXP-EXP-TIME upper-bound [CdAH,…]  EXP-SPACE lower-bound [our results] Cor: Any algorithm that manipulates winning strategies in explicit representation must use exponential space. … explicit representation: integer fractions

  11. Player 2 plays t Player 2 plays h  Player 2 plays h P • pi – probability of playing t in state i in -optimal strategy of Player 1. • Claim: 1) 0< pi < 1, for all i. • 2)pi<  , for all i. • 3)p1 ≤ p2 . p3 … pn • 4)pi ≤ pi+1 . pi+2 … pn t n pn pn-1 Purgatoryn t n-1 … t p3 p2 p1 3 t 2 t 1

  12. Open problems • Generic algorithm for -optimal strategy with symbolic representation? • How to redefine the game to be more realistic?

  13. Goals: Player 1 wants to reach a specific state or states. Player 2 wants to prevent Player 1 from reaching these states. Winning starting states: • Sure – Player 1 has a winning strategy that never fails. • Almost-Sure – Player 1 has a randomized strategy that reaches goal with probability 1. • Limit-Sure – For every  > 0, Player 1 has a strategy that reaches goal with probability at least 1 –  .

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