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The complexity of solving reachability games using value and strategy iteration Kristoffer Arnsfelt Hansen Rasmus Ibsen-Jensen   Peter Bro Miltersen Aarhus University Denmark CSR 2011, 14’th June
Overview ,[object Object],[object Object],[object Object],[object Object],[object Object],1/42
Matrix games   von Neumann 1928 2/42 0 1 -1 -1 0 1 1 -1 0
Matrix games   von Neumann 1928 2/42 0 1 -1 -1 0 1 1 -1 0
Concurrent reachability games  Everett 1957/de Alfaro, Henzinger, Kupferman 1998 Each entry can be either 0, 1 or a pointer vs. Dante* Lucifer* 0 1 * Naming convention from Hansen, Koucky and Miltersen, 2009 3/42 0 1 -1 -1 0 1 1 -1 0
Concurrent reachability games  Everett 1957/de Alfaro, Henzinger, Kupferman 1998 vs. Dante* Lucifer* Each entry can be either 0, 1 or a pointer * Naming convention from Hansen, Koucky and Miltersen, 2009 3/42
Concurrent reachability games  Everett 1957/de Alfaro, Henzinger, Kupferman 1998 Each entry can be either 0, 1 or a pointer 3/42
Concurrent reachability games  Everett 1957/de Alfaro, Henzinger, Kupferman 1998 Each entry can be either  0 , 1 or a pointer 3/42 0 0 0 0 0 0 0 0 0 0 0 0
Concurrent reachability games  Everett 1957/de Alfaro, Henzinger, Kupferman 1998 Each entry can be either 0,  1  or a pointer 3/42 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0
Concurrent reachability games  Everett 1957/de Alfaro, Henzinger, Kupferman 1998 Each entry can be either 0, 1 or  a pointer S: 3/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Concurrent reachability games  Everett 1957/de Alfaro, Henzinger, Kupferman 1998 Each entry can be either 0, 1 or a pointer S: 3/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Histories Each entry can be either 0, 1 or a pointer S: 4/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Histories and strategies ,[object Object],[object Object],[object Object],[object Object],[object Object],5/42
Payoffs ,[object Object],6/42
Everett 1957 Value of i 7/42
Algorithmic problems ,[object Object],[object Object],8/42
Value iteration  Shapley 1953 9/42 ,[object Object],[object Object]
Our results: Lower bound for value iteration ,[object Object],[object Object],[object Object],10/42
Our results: Upper bound for value iteration ,[object Object],[object Object],11/42
Value iteration example – G 0 S: 12/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Value iteration example – G 0 S: 0 0 0 0 12/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Value iteration example – G 1 S: 0 0 0 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
Value iteration example – G 1 S: 0 0 0 0 0 0 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
Value iteration example – G 1 S: 0 0 0 0 1 1 1 1 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1 0 0 0
Value iteration example – G 1 S: 0 0 0 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1 1 0 0 1 0 1
Value iteration example – G 1 S: 0 0 0 0 0 0 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1 1 0 0 1 0 1
Value iteration example – G 1 0 S: 0.33333/ 0 0 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1 1 0 0 0 1 0 0 0 1
Value iteration example – G 1 S: 0 0 0.33333/ 0 0 0 0 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
Value iteration example – G 1 S: 0 0 0 0 0 0 0 0 0 0.33333/ 0 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1 0 0 0
Value iteration example – G 1 S: 0 0.33333/ 0 0 0/ 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1 0 0 0 0 0 0 0 0 0
Value iteration example – G 1 S: 0 0 0 0.33333/ 0 0/ 0/ 0/ 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
Value iteration example – G 2 S: 0 0 0 0.33333/ 0.33333 0.11111/ 0/ 0/ 14/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
Value iteration example – G 3 S: 0.11111 0 0 0.33333/ 0.33333 0.11111/ 0/ 0.03704/ 15/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
Value iteration example – G 4 S: 0.11111 0.03704 0 0.33333/ 0.33333 0.11111/ 0.01235/ 0.03704/ 16/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
Value iteration example – G 5 S: 0.11111 0.03704 0.01235 0.33748/ 0.33333 0.11533/ 0.01754/ 0.04147/ 17/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
Value iteration example – G 6 S: 0.11533 0.04147 0.01754 0.33925/ 0.33748 0.11855/ 0.02172/ 0.04493/ 18/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
Value iteration example – G 7 S: 0.11855 0.04493 0.02172 0.34068/ 0.33925 0.12064/ 0.02519/ 0.04772/ 19/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
Value iteration example – G 8 S: 0.12064 0.04772 0.02519 0.34187/ 0.34068 0.12388/ 0.02815/ 0.04991/ 20/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
Value iteration example – G 9 S: 0.12388 0.04991 0.02815 0.34378/ 0.34187 0.12517/ 0.03070/ 0.05129 / 21/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
Strategy iteration Chatterjee, de Alfaro, Henzinger ’06 22/42 Was conjectured to be fast
Our results: Upper bound for strategy iteration ,[object Object],[object Object],23/42
Our results: Lower bound for strategy iteration ,[object Object],[object Object],[object Object],24/42 Strategy iteration, m=2 18446744073709551617 7 340282366920938463463374607431768211457 8 115792089237316195423570985008687907853269984665640564039457584007913129639937 9 Number of iterations needed to get over 1/2 N
Strategy iteration: Before iteration 1 S: ,[object Object],25/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Before iteration 1 S ,[object Object],0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 25/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 1 ,[object Object],[object Object],[object Object],S 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 26/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 1 ,[object Object],[object Object],[object Object],S 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 26/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 ,[object Object],[object Object],[object Object],S 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 26/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 1 1 0.66667 The numbers on the edges are the probability that the edge is used. Edges without a number have probability 0.33333 to be used. ,[object Object],[object Object],[object Object],S 0 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 26/42 S 0 0 0 S 0 S S 0 0 S 0 S S 0 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 1 0 1 0.66667 The numbers on the edges are the probability that the edge is used. Edges without a number have probability 0.33333 to be used. 0.66667 0.66667 0.66667 0.66667 0.66667 0.66667 0.66667 ,[object Object],[object Object],[object Object],26/42
Strategy iteration: Iteration 1 ,[object Object],[object Object],[object Object],S 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 26/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 1 0.11111 0.03704 0.01235 0.33333 S ,[object Object],[object Object],[object Object],0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 26/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 1 0.11111 0.03704 0.01235 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.01235 0 0 0 S 1 1 1 ,[object Object],[object Object],[object Object],0.01235 0.01235 0.01235 0.33748 26/42 1 0 0 S 1 0 S S 1 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 1 S 0.11111 0.03704 0.01235 0.33333 0.33748 0.33332 0.32920 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 0.33333 26/42 ,[object Object],[object Object],[object Object],1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 1 S ,[object Object],[object Object],[object Object],0.11111 0.03704 0.01235 0.33333 0.33748 0.33332 0.32920 0.34599 0.33317 0.32084 0.37327 0.33180 0.29493 0.47368 0.31579 0.21053 26/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 2 S ,[object Object],[object Object],[object Object],0.11111 0.03704 0.01235 0.33333 0.33748 0.33332 0.32920 0.34599 0.33317 0.32084 0.37327 0.33180 0.29493 0.47368 0.31579 0.21053 27/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 2 S ,[object Object],[object Object],[object Object],0.11111 0.03704 0.01235 0.33333 0.33748 0.33332 0.32920 0.34599 0.33317 0.32084 0.37327 0.33180 0.29493 0.47368 0.31579 0.21053 27/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 2 S ,[object Object],[object Object],[object Object],0.11111 0.03704 0.01235 0.33333 0.33748 0.33332 0.32920 0.34599 0.33317 0.32084 0.37327 0.33180 0.29493 0.47368 0.31579 0.21053 27/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 2 S ,[object Object],[object Object],[object Object],0.11677 0.04359 0.02065 0.33748 0.33748 0.33332 0.32920 0.34599 0.33317 0.32084 0.37327 0.33180 0.29493 0.47368 0.31579 0.21053 27/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 2 S ,[object Object],[object Object],[object Object],0.11677 0.04359 0.02065 0.33748 0.34031 0.33329 0.32640 0.35458 0.33289 0.31253 0.39987 0.33180 0.32917 0.55453 0.29186 0.15361 27/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 3 S ,[object Object],[object Object],[object Object],0.11677 0.04359 0.02065 0.33748 0.34031 0.33329 0.32640 0.35458 0.33289 0.31253 0.39987 0.33180 0.32917 0.55453 0.29186 0.15361 28/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 3 S ,[object Object],[object Object],[object Object],0.11677 0.04359 0.02065 0.33748 0.34031 0.33329 0.32640 0.35458 0.33289 0.31253 0.39987 0.33180 0.32917 0.55453 0.29186 0.15361 28/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 3 S ,[object Object],[object Object],[object Object],0.11677 0.04359 0.02065 0.33748 0.34031 0.33329 0.32640 0.35458 0.33289 0.31253 0.39987 0.33180 0.32917 0.55453 0.29186 0.15361 28/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 3 S ,[object Object],[object Object],[object Object],0.12067 0.04825 0.02676 0.34031 0.34031 0.33329 0.32640 0.35458 0.33289 0.31253 0.39987 0.33180 0.32917 0.55453 0.29186 0.15361 28/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 3 S ,[object Object],[object Object],[object Object],0.12067 0.04825 0.02676 0.34031 0.34031 0.33329 0.32640 0.35458 0.33289 0.31253 0.39987 0.33180 0.32917 0.55453 0.29186 0.15361 28/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 3 S ,[object Object],[object Object],[object Object],0.12067 0.04825 0.02676 0.34031 0.34241 0.33325 0.32434 0.36097 0.33259 0.30644 0.41947 0.32646 0.25407 0.60831 0.27098 0.12071 28/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 4 S ,[object Object],[object Object],[object Object],0.12067 0.04825 0.02676 0.34031 0.34241 0.33325 0.32434 0.36097 0.33259 0.30644 0.41947 0.32646 0.25407 0.60831 0.27098 0.12071 29/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 4 S ,[object Object],[object Object],[object Object],0.12067 0.04825 0.02676 0.34031 0.34241 0.33325 0.32434 0.36097 0.33259 0.30644 0.41947 0.32646 0.25407 0.60831 0.27098 0.12071 29/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 4 S ,[object Object],[object Object],[object Object],0.12067 0.04825 0.02676 0.34031 0.34241 0.33325 0.32434 0.36097 0.33259 0.30644 0.41947 0.32646 0.25407 0.60831 0.27098 0.12071 29/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 4 S ,[object Object],[object Object],[object Object],0.12067 0.04825 0.02676 0.34031 0.34241 0.33325 0.32434 0.36097 0.33259 0.30644 0.41947 0.32646 0.25407 0.60831 0.27098 0.12071 29/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 4 S ,[object Object],[object Object],[object Object],0.12360 0.05185 0.03154 0.34241 0.34241 0.33325 0.32434 0.36097 0.33259 0.30644 0.41947 0.32646 0.25407 0.60831 0.27098 0.12071 29/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 4 S ,[object Object],[object Object],[object Object],0.12360 0.05185 0.03154 0.34241 0.34241 0.33325 0.32434 0.36097 0.33259 0.30644 0.41947 0.32646 0.25407 0.60831 0.27098 0.12071 29/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 4 S ,[object Object],[object Object],[object Object],0.12360 0.05185 0.03154 0.34241 0.34407 0.33322 0.32271 0.36601 0.33230 0.30169 0.43486 0.32390 0.24125 0.64720 0.25350 0.09930 29/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 5 S ,[object Object],[object Object],[object Object],0.12360 0.05185 0.03154 0.34241 0.34407 0.33322 0.32271 0.36601 0.33230 0.30169 0.43486 0.32390 0.24125 0.64720 0.25350 0.09930 30/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 5 S ,[object Object],[object Object],[object Object],0.12360 0.05185 0.03154 0.34241 0.34407 0.33322 0.32271 0.36601 0.33230 0.30169 0.43486 0.32390 0.24125 0.64720 0.25350 0.09930 30/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 5 S ,[object Object],[object Object],[object Object],0.12360 0.05185 0.03154 0.34241 0.34407 0.33322 0.32271 0.36601 0.33230 0.30169 0.43486 0.32390 0.24125 0.64720 0.25350 0.09930 30/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 5 S ,[object Object],[object Object],[object Object],0.12593 0.05476 0.03544 0.34407 0.34407 0.33322 0.32271 0.36601 0.33230 0.30169 0.43486 0.32390 0.24125 0.64720 0.25350 0.09930 30/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 5 S ,[object Object],[object Object],[object Object],0.12593 0.05476 0.03544 0.34407 0.34543 0.33319 0.32138 0.37015 0.33202 0.29783 0.44745 0.32152 0.23103 0.67692 0.23882 0.08426 30/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 6 S ,[object Object],[object Object],[object Object],0.12593 0.05476 0.03544 0.34407 0.34543 0.33319 0.32138 0.37015 0.33202 0.29783 0.44745 0.32152 0.23103 0.67692 0.23882 0.08426 31/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 6 S ,[object Object],[object Object],[object Object],0.12593 0.05476 0.03544 0.34407 0.34543 0.33319 0.32138 0.37015 0.33202 0.29783 0.44745 0.32152 0.23103 0.67692 0.23882 0.08426 31/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 6 S ,[object Object],[object Object],[object Object],0.12593 0.05476 0.03544 0.34407 0.34543 0.33319 0.32138 0.37015 0.33202 0.29783 0.44745 0.32152 0.23103 0.67692 0.23882 0.08426 31/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 6 S ,[object Object],[object Object],[object Object],0.12786 0.05721 0.03873 0.34543 0.34543 0.33319 0.32138 0.37015 0.33202 0.29783 0.44745 0.32152 0.23103 0.67692 0.23882 0.08426 31/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 6 S ,[object Object],[object Object],[object Object],0.12786 0.05721 0.03873 0.34543 0.34543 0.33319 0.32138 0.37015 0.33202 0.29783 0.44745 0.32152 0.23103 0.67692 0.23882 0.08426 31/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 6 S ,[object Object],[object Object],[object Object],0.12786 0.05721 0.03873 0.34543 0.34658 0.33316 0.32026 0.37366 0.33177 0.29457 0.45807 0.31933 0.22260 0.70055 0.22633 0.07312 31/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 6 S ,[object Object],[object Object],[object Object],0.12786 0.05721 0.03873 0.34543 0.34658 0.33316 0.32026 0.37366 0.33177 0.29457 0.45807 0.31933 0.22260 0.70055 0.22633 0.07312 31/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 7 S ,[object Object],[object Object],[object Object],0.12786 0.05721 0.03873 0.34543 0.34658 0.33316 0.32026 0.37366 0.33177 0.29457 0.45807 0.31933 0.22260 0.70055 0.22633 0.07312 32/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 7 S ,[object Object],[object Object],[object Object],0.12786 0.05721 0.03873 0.34543 0.34658 0.33316 0.32026 0.37366 0.33177 0.29457 0.45807 0.31933 0.22260 0.70055 0.22633 0.07312 32/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 7 S ,[object Object],[object Object],[object Object],0.12950 0.05932 0.04156 0.34658 0.34658 0.33316 0.32026 0.37366 0.33177 0.29457 0.45807 0.31933 0.22260 0.70055 0.22633 0.07312 32/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 7 S ,[object Object],[object Object],[object Object],0.12950 0.05932 0.04156 0.34658 0.34658 0.33316 0.32026 0.37366 0.33177 0.29457 0.45807 0.31933 0.22260 0.70055 0.22633 0.07312 32/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 7 S ,[object Object],[object Object],[object Object],0.12950 0.05932 0.04156 0.34658 0.34758 0.33313 0.31929 0.37670 0.33153 0.29177 0.46723 0.31730 0.21547 0.71988 0.21557 0.06455 32/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 8 S ,[object Object],[object Object],[object Object],0.12950 0.05932 0.04156 0.34658 0.34758 0.33313 0.31929 0.37670 0.33153 0.29177 0.46723 0.31730 0.21547 0.71988 0.21557 0.06455 33/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 8 S ,[object Object],[object Object],[object Object],0.12950 0.05932 0.04156 0.34658 0.34758 0.33313 0.31929 0.37670 0.33153 0.29177 0.46723 0.31730 0.21547 0.71988 0.21557 0.06455 33/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 8 S ,[object Object],[object Object],[object Object],0.12950 0.05932 0.04156 0.34658 0.34758 0.33313 0.31929 0.37670 0.33153 0.29177 0.46723 0.31730 0.21547 0.71988 0.21557 0.06455 33/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 8 S ,[object Object],[object Object],[object Object],0.13093 0.06118 0.04404 0.34758 0.34758 0.33313 0.31929 0.37670 0.33153 0.29177 0.46723 0.31730 0.21547 0.71988 0.21557 0.06455 33/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 8 S ,[object Object],[object Object],[object Object],0.13093 0.06118 0.04404 0.34758 0.34845 0.33311 0.31844 0.37937 0.33130 0.28933 0.47527 0.31541 0.20932 0.73606 0.20618 0.05776 33/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 9 S ,[object Object],[object Object],[object Object],0.13093 0.06118 0.04404 0.34758 0.34845 0.33311 0.31844 0.37937 0.33130 0.28933 0.47527 0.31541 0.20932 0.73606 0.20618 0.05776 34/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 9 S ,[object Object],[object Object],[object Object],0.13093 0.06118 0.04404 0.34758 0.34845 0.33311 0.31844 0.37937 0.33130 0.28933 0.47527 0.31541 0.20932 0.73606 0.20618 0.05776 34/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 9 S ,[object Object],[object Object],[object Object],0.13093 0.06118 0.04404 0.34758 0.34845 0.33311 0.31844 0.37937 0.33130 0.28933 0.47527 0.31541 0.20932 0.73606 0.20618 0.05776 34/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 9 S ,[object Object],[object Object],[object Object],0.13219 0.06283 0.04624 0.34845 0.34845 0.33311 0.31844 0.37937 0.33130 0.28933 0.47527 0.31541 0.20932 0.73606 0.20618 0.05776 34/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 9 S ,[object Object],[object Object],[object Object],0.13219 0.06283 0.04624 0.34845 0.34845 0.33311 0.31844 0.37937 0.33130 0.28933 0.47527 0.31541 0.20932 0.73606 0.20618 0.05776 34/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Strategy iteration: Iteration 9 S ,[object Object],[object Object],[object Object],0.13219 0.06283 0.04624 0.34845 0.34923 0.33309 0.31768 0.38176 0.33109 0.28715 0.48241 0.31366 0.20393 0.74985 0.19791 0.05224 34/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
Generalized Purgatory P(N,m) ,[object Object],[object Object],[object Object],[object Object],35/42
Interesting fact ,[object Object],36/42
Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices 37/42 1 0 1 0 0 1 0 1 1 0 1
Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix t:=0 Strategy iteration on 3 matrices 37/42 1 0 1 0 0 1 0 1 1 0 1
Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=0 0 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 37/42 1 0 1 0 0 1 0 1 1 0 1
Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=1 0 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 38/42 1 0 1 0 0 1 0 1 1 0 1
Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=1 0 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 38/42 1 0 1 0 0 1 0 1 1 0 1
Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=1 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.25 0.125 38/42 1 0 1 0 0 1 0 1 1 0 1
Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=1 0.5 0.66667  0.33333  0.66667  0.33333  0.57143  0.42857  0.53333  0.46667  0.5 0.5 0.25 0.125 38/42 1 0 1 1 0 1 0 0 1 0 1
Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=2 0.5 0.66667  0.33333  0.66667  0.33333  0.57143  0.42857  0.53333  0.46667  0.5 0.5 0.25 0.125 39/42 1 0 1 1 0 1 0 0 1 0 1
Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=2 0.5 0.66667  0.33333  0.66667  0.33333  0.57143  0.42857  0.53333  0.46667  0.5 0.5 0.25 0.125 39/42 1 0 1 1 0 1 0 0 1 0 1
Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=2 0.66667 0.66667  0.33333  0.66667  0.33333  0.57143  0.42857  0.53333  0.46667  0.66667 0.53333  0.30476  0.20317  39/42 1 0 1 1 0 1 0 0 1 0 1
Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=2 0.66667 0.75000 0.25000 0.75000 0.25000  0.61765  0.38235  0.55654  0.44346  0.66667 0.53333  0.30476  0.20317  39/42 1 0 1 1 0 1 0 0 1 0 1
Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=3 0.66667 0.75000 0.25000 0.75000 0.25000  0.61765  0.38235  0.55654  0.44346  0.66667 0.53333  0.30476  0.20317  40/42 1 0 1 1 0 1 0 0 1 0 1
Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=3 0.66667 0.75000 0.25000 0.75000 0.25000  0.61765  0.38235  0.55654  0.44346  0.66667 0.53333  0.30476  0.20317  40/42 1 0 1 1 0 1 0 0 1 0 1
Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=3 0.75000 0.75000 0.25000 0.75000 0.25000  0.61765  0.38235  0.55654  0.44346  0.75000 0.55654  0.34374  0.25781 40/42 1 0 1 1 0 1 0 0 1 0 1
Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=3 0.75000 0.80000 0.20000 0.80000 0.20000  0.65072  0.34928  0.57399  0.42601  0.75000 0.55654  0.34374  0.25781 41/42 1 0 1 1 0 1 0 0 1 0 1
The end ,[object Object],[object Object],[object Object],[object Object],42/42

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Csr2011 june14 16_30_ibsen-jensen

  • 1. The complexity of solving reachability games using value and strategy iteration Kristoffer Arnsfelt Hansen Rasmus Ibsen-Jensen Peter Bro Miltersen Aarhus University Denmark CSR 2011, 14’th June
  • 2.
  • 3. Matrix games von Neumann 1928 2/42 0 1 -1 -1 0 1 1 -1 0
  • 4. Matrix games von Neumann 1928 2/42 0 1 -1 -1 0 1 1 -1 0
  • 5. Concurrent reachability games Everett 1957/de Alfaro, Henzinger, Kupferman 1998 Each entry can be either 0, 1 or a pointer vs. Dante* Lucifer* 0 1 * Naming convention from Hansen, Koucky and Miltersen, 2009 3/42 0 1 -1 -1 0 1 1 -1 0
  • 6. Concurrent reachability games Everett 1957/de Alfaro, Henzinger, Kupferman 1998 vs. Dante* Lucifer* Each entry can be either 0, 1 or a pointer * Naming convention from Hansen, Koucky and Miltersen, 2009 3/42
  • 7. Concurrent reachability games Everett 1957/de Alfaro, Henzinger, Kupferman 1998 Each entry can be either 0, 1 or a pointer 3/42
  • 8. Concurrent reachability games Everett 1957/de Alfaro, Henzinger, Kupferman 1998 Each entry can be either 0 , 1 or a pointer 3/42 0 0 0 0 0 0 0 0 0 0 0 0
  • 9. Concurrent reachability games Everett 1957/de Alfaro, Henzinger, Kupferman 1998 Each entry can be either 0, 1 or a pointer 3/42 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0
  • 10. Concurrent reachability games Everett 1957/de Alfaro, Henzinger, Kupferman 1998 Each entry can be either 0, 1 or a pointer S: 3/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
  • 11. Concurrent reachability games Everett 1957/de Alfaro, Henzinger, Kupferman 1998 Each entry can be either 0, 1 or a pointer S: 3/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
  • 12. Histories Each entry can be either 0, 1 or a pointer S: 4/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
  • 13.
  • 14.
  • 15. Everett 1957 Value of i 7/42
  • 16.
  • 17.
  • 18.
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  • 20. Value iteration example – G 0 S: 12/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
  • 21. Value iteration example – G 0 S: 0 0 0 0 12/42 1 0 0 S 1 0 S S 1 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S
  • 22. Value iteration example – G 1 S: 0 0 0 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
  • 23. Value iteration example – G 1 S: 0 0 0 0 0 0 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
  • 24. Value iteration example – G 1 S: 0 0 0 0 1 1 1 1 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1 0 0 0
  • 25. Value iteration example – G 1 S: 0 0 0 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1 1 0 0 1 0 1
  • 26. Value iteration example – G 1 S: 0 0 0 0 0 0 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1 1 0 0 1 0 1
  • 27. Value iteration example – G 1 0 S: 0.33333/ 0 0 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1 1 0 0 0 1 0 0 0 1
  • 28. Value iteration example – G 1 S: 0 0 0.33333/ 0 0 0 0 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
  • 29. Value iteration example – G 1 S: 0 0 0 0 0 0 0 0 0 0.33333/ 0 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1 0 0 0
  • 30. Value iteration example – G 1 S: 0 0.33333/ 0 0 0/ 0 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1 0 0 0 0 0 0 0 0 0
  • 31. Value iteration example – G 1 S: 0 0 0 0.33333/ 0 0/ 0/ 0/ 13/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
  • 32. Value iteration example – G 2 S: 0 0 0 0.33333/ 0.33333 0.11111/ 0/ 0/ 14/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
  • 33. Value iteration example – G 3 S: 0.11111 0 0 0.33333/ 0.33333 0.11111/ 0/ 0.03704/ 15/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
  • 34. Value iteration example – G 4 S: 0.11111 0.03704 0 0.33333/ 0.33333 0.11111/ 0.01235/ 0.03704/ 16/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
  • 35. Value iteration example – G 5 S: 0.11111 0.03704 0.01235 0.33748/ 0.33333 0.11533/ 0.01754/ 0.04147/ 17/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
  • 36. Value iteration example – G 6 S: 0.11533 0.04147 0.01754 0.33925/ 0.33748 0.11855/ 0.02172/ 0.04493/ 18/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
  • 37. Value iteration example – G 7 S: 0.11855 0.04493 0.02172 0.34068/ 0.33925 0.12064/ 0.02519/ 0.04772/ 19/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
  • 38. Value iteration example – G 8 S: 0.12064 0.04772 0.02519 0.34187/ 0.34068 0.12388/ 0.02815/ 0.04991/ 20/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
  • 39. Value iteration example – G 9 S: 0.12388 0.04991 0.02815 0.34378/ 0.34187 0.12517/ 0.03070/ 0.05129 / 21/42 0 0 S 0 S S 0 0 S 0 S S 0 0 S 0 S S 1 0 0 S 1 0 S S 1
  • 40. Strategy iteration Chatterjee, de Alfaro, Henzinger ’06 22/42 Was conjectured to be fast
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  • 103. Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices 37/42 1 0 1 0 0 1 0 1 1 0 1
  • 104. Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix t:=0 Strategy iteration on 3 matrices 37/42 1 0 1 0 0 1 0 1 1 0 1
  • 105. Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=0 0 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 37/42 1 0 1 0 0 1 0 1 1 0 1
  • 106. Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=1 0 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 38/42 1 0 1 0 0 1 0 1 1 0 1
  • 107. Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=1 0 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 38/42 1 0 1 0 0 1 0 1 1 0 1
  • 108. Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=1 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.25 0.125 38/42 1 0 1 0 0 1 0 1 1 0 1
  • 109. Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=1 0.5 0.66667 0.33333 0.66667 0.33333 0.57143 0.42857 0.53333 0.46667 0.5 0.5 0.25 0.125 38/42 1 0 1 1 0 1 0 0 1 0 1
  • 110. Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=2 0.5 0.66667 0.33333 0.66667 0.33333 0.57143 0.42857 0.53333 0.46667 0.5 0.5 0.25 0.125 39/42 1 0 1 1 0 1 0 0 1 0 1
  • 111. Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=2 0.5 0.66667 0.33333 0.66667 0.33333 0.57143 0.42857 0.53333 0.46667 0.5 0.5 0.25 0.125 39/42 1 0 1 1 0 1 0 0 1 0 1
  • 112. Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=2 0.66667 0.66667 0.33333 0.66667 0.33333 0.57143 0.42857 0.53333 0.46667 0.66667 0.53333 0.30476 0.20317 39/42 1 0 1 1 0 1 0 0 1 0 1
  • 113. Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=2 0.66667 0.75000 0.25000 0.75000 0.25000 0.61765 0.38235 0.55654 0.44346 0.66667 0.53333 0.30476 0.20317 39/42 1 0 1 1 0 1 0 0 1 0 1
  • 114. Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=3 0.66667 0.75000 0.25000 0.75000 0.25000 0.61765 0.38235 0.55654 0.44346 0.66667 0.53333 0.30476 0.20317 40/42 1 0 1 1 0 1 0 0 1 0 1
  • 115. Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=3 0.66667 0.75000 0.25000 0.75000 0.25000 0.61765 0.38235 0.55654 0.44346 0.66667 0.53333 0.30476 0.20317 40/42 1 0 1 1 0 1 0 0 1 0 1
  • 116. Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=3 0.75000 0.75000 0.25000 0.75000 0.25000 0.61765 0.38235 0.55654 0.44346 0.75000 0.55654 0.34374 0.25781 40/42 1 0 1 1 0 1 0 0 1 0 1
  • 117. Exemplifying important facts Value iteration on 1 matrix Strategy iteration on 1 matrix Strategy iteration on 3 matrices t:=3 0.75000 0.80000 0.20000 0.80000 0.20000 0.65072 0.34928 0.57399 0.42601 0.75000 0.55654 0.34374 0.25781 41/42 1 0 1 1 0 1 0 0 1 0 1
  • 118.