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Synthesizing Optimally Resilient Controllers Joint work with Daniel Neider and Alexander Weinert Martin Zimmermann Saarland University September 20th, 2018 Highlights Conference, Berlin, Germany Martin Zimmermann Saarland University


  1. Synthesizing Optimally Resilient Controllers Joint work with Daniel Neider and Alexander Weinert Martin Zimmermann Saarland University September 20th, 2018 Highlights Conference, Berlin, Germany Martin Zimmermann Saarland University Synthesizing Optimally Resilient Controllers

  2. Dallal, Neider, Tabuada: Safety games with “unmodeled intermittent disturbances” Add disturbance edges (dashed) to classical safety game Only from Player 0 vertices Not under control of Player 1 nor equipped with fault model Instead: assumed to be “rare” events Question: how many disturbances can Player 0 deal with? Martin Zimmermann Saarland University Synthesizing Optimally Resilient Controllers

  3. Dallal, Neider, Tabuada: Safety games with “unmodeled intermittent disturbances” Definition The resilience of a vertex v is the largest k such that Player 0 has a strategy σ such that every play that starts in v , is consistent with σ , and has strictly less than k disturbances is winning for Player 0. Martin Zimmermann Saarland University Synthesizing Optimally Resilient Controllers

  4. Dallal, Neider, Tabuada: Safety games with “unmodeled intermittent disturbances” ∞ 1 2 1 0 2 Definition The resilience of a vertex v is the largest k such that Player 0 has a strategy σ such that every play that starts in v , is consistent with σ , and has strictly less than k disturbances is winning for Player 0. Martin Zimmermann Saarland University Synthesizing Optimally Resilient Controllers

  5. Dallal, Neider, Tabuada: Safety games with “unmodeled intermittent disturbances” ∞ 1 2 1 0 2 Theorem (DNT’16) The resilience of the vertices of a safety game G and a memoryless optimally resilient strategy for G are computable in polynomial time. Martin Zimmermann Saarland University Synthesizing Optimally Resilient Controllers

  6. Neider, Weinert, Z. (’17) : What about (max-) parity games? 1 1 2 1 1 0 Martin Zimmermann Saarland University Synthesizing Optimally Resilient Controllers

  7. Neider, Weinert, Z. (’17) : What about (max-) parity games? 1 0 1 1 2 1 1 0 0 0 Martin Zimmermann Saarland University Synthesizing Optimally Resilient Controllers

  8. Neider, Weinert, Z. (’17) : What about (max-) parity games? 1 0 1 1 2 1 1 0 0 0 Definition The resilience of a vertex v is the largest k such that Player 0 has a strategy σ such that every play that starts in v , is consistent with σ , and has strictly less than k disturbances is winning for Player 0. Martin Zimmermann Saarland University Synthesizing Optimally Resilient Controllers

  9. Neider, Weinert, Z. (’17) : What about (max-) parity games? ω 1 ω 1 0 1 1 2 1 1 2 ω + 1 ω + 1 1 0 1 1 0 0 0 Definition The resilience of a vertex v is the largest k such that Player 0 has a strategy σ such that every play that starts in v , is consistent with σ , and has strictly less than k disturbances is winning for Player 0. Martin Zimmermann Saarland University Synthesizing Optimally Resilient Controllers

  10. Neider, Weinert, Z. (’17) : What about (max-) parity games? ω 1 ω 1 0 1 1 2 1 1 2 ω + 1 ω + 1 1 0 1 1 0 0 0 Theorem (NWZ’18) The resilience of the vertices of a parity game G and a memoryless optimally resilient strategy for G are computable in quasi-polynomial time. Martin Zimmermann Saarland University Synthesizing Optimally Resilient Controllers

  11. Disturbances make games more interesting! 1 0 0 1 0 1 0 1 0 ω + 1 Disturbances can be desirable: From upper vertex, one disturbance takes Player 0 from her opponent’s winning region to her own From the lower vertex, there is no such chance for recovery Note that both vertices have resilience 0 Martin Zimmermann Saarland University Synthesizing Optimally Resilient Controllers

  12. Disturbances make games more interesting! 0 0 0 ω ω ω 0 ω ω ω ω 0 0 1 Tradeo ff : disturbances vs. winning condition If odd colors are to be avoided, then the upper route is preferable (it takes two consecutive disturbances to reach 1) If disturbances are to be avoided, then the lower route is preferable (only one disturbance possible) Note that both strategies witness all vertices having resilience ω Martin Zimmermann Saarland University Synthesizing Optimally Resilient Controllers

  13. Disturbances make games more interesting! 1 1 2 1 1 0 Tradeo ff : disturbances vs. memory The more memory Player 0 uses, the more she can avoid the risk of a fatal disturbance, but she has to take the risk infinitely often to satisfy the parity condition. Martin Zimmermann Saarland University Synthesizing Optimally Resilient Controllers

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