1,969 research outputs found
An Exponential Lower Bound for the Latest Deterministic Strategy Iteration Algorithms
This paper presents a new exponential lower bound for the two most popular
deterministic variants of the strategy improvement algorithms for solving
parity, mean payoff, discounted payoff and simple stochastic games. The first
variant improves every node in each step maximizing the current valuation
locally, whereas the second variant computes the globally optimal improvement
in each step. We outline families of games on which both variants require
exponentially many strategy iterations
The Fixpoint-Iteration Algorithm for Parity Games
It is known that the model checking problem for the modal mu-calculus reduces
to the problem of solving a parity game and vice-versa. The latter is realised
by the Walukiewicz formulas which are satisfied by a node in a parity game iff
player 0 wins the game from this node. Thus, they define her winning region,
and any model checking algorithm for the modal mu-calculus, suitably
specialised to the Walukiewicz formulas, yields an algorithm for solving parity
games. In this paper we study the effect of employing the most straight-forward
mu-calculus model checking algorithm: fixpoint iteration. This is also one of
the few algorithms, if not the only one, that were not originally devised for
parity game solving already. While an empirical study quickly shows that this
does not yield an algorithm that works well in practice, it is interesting from
a theoretical point for two reasons: first, it is exponential on virtually all
families of games that were designed as lower bounds for very particular
algorithms suggesting that fixpoint iteration is connected to all those.
Second, fixpoint iteration does not compute positional winning strategies. Note
that the Walukiewicz formulas only define winning regions; some additional work
is needed in order to make this algorithm compute winning strategies. We show
that these are particular exponential-space strategies which we call
eventually-positional, and we show how positional ones can be extracted from
them.Comment: In Proceedings GandALF 2014, arXiv:1408.556
Symmetric Strategy Improvement
Symmetry is inherent in the definition of most of the two-player zero-sum
games, including parity, mean-payoff, and discounted-payoff games. It is
therefore quite surprising that no symmetric analysis techniques for these
games exist. We develop a novel symmetric strategy improvement algorithm where,
in each iteration, the strategies of both players are improved simultaneously.
We show that symmetric strategy improvement defies Friedmann's traps, which
shook the belief in the potential of classic strategy improvement to be
polynomial
Strategy Derivation for Small Progress Measures
Small Progress Measures is one of the most efficient parity game solving
algorithms. The original algorithm provides the full solution (winning regions
and strategies) in
time, and requires a re-run of the algorithm on one of the winning regions. We
provide a novel operational interpretation of progress measures, and modify the
algorithm so that it derives the winning strategies for both players in one
pass. This reduces the upper bound on strategy derivation for SPM to .Comment: polished the tex
Permutation Games for the Weakly Aconjunctive -Calculus
We introduce a natural notion of limit-deterministic parity automata and
present a method that uses such automata to construct satisfiability games for
the weakly aconjunctive fragment of the -calculus. To this end we devise a
method that determinizes limit-deterministic parity automata of size with
priorities through limit-deterministic B\"uchi automata to deterministic
parity automata of size and with
priorities. The construction relies on limit-determinism to avoid the full
complexity of the Safra/Piterman-construction by using partial permutations of
states in place of Safra-Trees. By showing that limit-deterministic parity
automata can be used to recognize unsuccessful branches in pre-tableaux for the
weakly aconjunctive -calculus, we obtain satisfiability games of size
with priorities for weakly aconjunctive
input formulas of size and alternation-depth . A prototypical
implementation that employs a tableau-based global caching algorithm to solve
these games on-the-fly shows promising initial results
The Rabin index of parity games
We study the descriptive complexity of parity games by taking into account
the coloring of their game graphs whilst ignoring their ownership structure.
Colored game graphs are identified if they determine the same winning regions
and strategies, for all ownership structures of nodes. The Rabin index of a
parity game is the minimum of the maximal color taken over all equivalent
coloring functions. We show that deciding whether the Rabin index is at least k
is in PTIME for k=1 but NP-hard for all fixed k > 1. We present an EXPTIME
algorithm that computes the Rabin index by simplifying its input coloring
function. When replacing simple cycle with cycle detection in that algorithm,
its output over-approximates the Rabin index in polynomial time. Experimental
results show that this approximation yields good values in practice.Comment: In Proceedings GandALF 2013, arXiv:1307.416
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