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Theoretical computer science

Quasipolynomial algorithms for mean-payoff, stochastic and parity games

OpenAI research collection · 4 manuscripts · Source checked 2026-10-19

OpenAI's result summary

Gives deterministic algorithms using 2^{O((log(L+2))^2)} bit operations, for complete binary input length L, for ordinary mean-payoff games and two separate extensions. They compute exact values and optimal positional strategies in ordinary games, the nonnegative expectation-of-liminf value set in turn-based stochastic games, and the winning set for nonnegative liminf mean payoff conjoined with parity. Signed rewards, rational chance probabilities, and parity priorities are unrestricted and binary-encoded.

Read the manuscripts

Short excerpts below come from OpenAI's abstracts. The full abstract and original PDF preserve the paper's precise scope.

MANUSCRIPT 01

Turn-Based Stochastic Mean-Payoff Games in Deterministic Quasipolynomial Time

We give a uniform deterministic quasipolynomial-time algorithm for finite turn-based stochastic mean-payoff games with signed integer rewards and rational chance-transition probabilities encoded in binary. It computes exactly the vertices of nonnegative value, including value zero, for the expectation of the pathwise liminf…

Full source abstract

We give a uniform deterministic quasipolynomial-time algorithm for finite turn-based stochastic mean-payoff games with signed integer rewards and rational chance-transition probabilities encoded in binary. It computes exactly the vertices of nonnegative value, including value zero, for the expectation of the pathwise liminf mean payoff. The algorithm uses exact rational arithmetic and 2^{O((log(L+2))^2)} bit operations, where L is the complete binary input length.

This exact PDF is not listed in the imported formalization catalogue. Family scope notes may contain further information.

MANUSCRIPT 02

Mean-payoff parity games in quasipolynomial time

We give a uniform deterministic quasipolynomial-time algorithm for mean-payoff parity games. It computes all vertices from which a player can enforce both nonnegative liminf mean payoff and the parity condition, with arbitrary signed binary rewards and unrestricted binary priorities. The running time is 2^{O((log(L+2))^2)} bit…

Full source abstract

We give a uniform deterministic quasipolynomial-time algorithm for mean-payoff parity games. It computes all vertices from which a player can enforce both nonnegative liminf mean payoff and the parity condition, with arbitrary signed binary rewards and unrestricted binary priorities. The running time is 2^{O((log(L+2))^2)} bit operations, where L is the complete input length.

This exact PDF is not listed in the imported formalization catalogue. Family scope notes may contain further information.

MANUSCRIPT 03

Deterministic quasipolynomial-time mean-payoff games

We give a deterministic algorithm that computes the complete zero-threshold winning set of a finite mean-payoff game with arbitrary signed integer edge weights encoded in binary. For total explicit input length L, it uses 2^{O((log(L+2))^2)} bit operations. A reduction also computes the exact rational value at every vertex and…

Full source abstract

We give a deterministic algorithm that computes the complete zero-threshold winning set of a finite mean-payoff game with arbitrary signed integer edge weights encoded in binary. For total explicit input length L, it uses 2^{O((log(L+2))^2)} bit operations. A reduction also computes the exact rational value at every vertex and globally optimal positional strategies for both players within the same quasipolynomial bound.

This exact PDF is not listed in the imported formalization catalogue. Family scope notes may contain further information.

MANUSCRIPT 04

Randomized quasipolynomial-time mean-payoff games

We give a randomized algorithm that computes the complete zero-threshold winning set of a finite mean-payoff game with arbitrary signed integer edge weights encoded in binary. For total explicit input length L, it uses 2^{O((log(L+2))^2)} bit operations on every random tape and is correct with probability at least 7/8. A…

Full source abstract

We give a randomized algorithm that computes the complete zero-threshold winning set of a finite mean-payoff game with arbitrary signed integer edge weights encoded in binary. For total explicit input length L, it uses 2^{O((log(L+2))^2)} bit operations on every random tape and is correct with probability at least 7/8. A polynomial-time check certifies the winning regions and positional strategies for both players or reports failure. Independent repetition therefore gives an always-correct algorithm with the same expected quasipolynomial bit bound.

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