On the Complexity of Rational Verification
- URL: http://arxiv.org/abs/2207.02637v1
- Date: Wed, 6 Jul 2022 12:56:22 GMT
- Title: On the Complexity of Rational Verification
- Authors: Julian Gutierrez, Muhammad Najib, Giuseppe Perelli, Michael Wooldridge
- Abstract summary: Rational verification refers to the problem of checking which temporal logic properties hold of a concurrent multiagent system.
We show that the complexity of rational verification can be greatly reduced by specifications.
We provide improved results for rational verification when considering players' goals given by mean-payoff utility functions.
- Score: 5.230352342979224
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Rational verification refers to the problem of checking which temporal logic
properties hold of a concurrent multiagent system, under the assumption that
agents in the system choose strategies that form a game-theoretic equilibrium.
Rational verification can be understood as a counterpart to model checking for
multiagent systems, but while classical model checking can be done in
polynomial time for some temporal logic specification languages such as CTL,
and polynomial space with LTL specifications, rational verification is much
harder: the key decision problems for rational verification are
2EXPTIME-complete with LTL specifications, even when using explicit-state
system representations. Against this background, our contributions in this
paper are threefold. First, we show that the complexity of rational
verification can be greatly reduced by restricting specifications to GR(1), a
fragment of LTL that can represent a broad and practically useful class of
response properties of reactive systems. In particular, we show that for a
number of relevant settings, rational verification can be done in polynomial
space and even in polynomial time. Second, we provide improved complexity
results for rational verification when considering players' goals given by
mean-payoff utility functions; arguably the most widely used approach for
quantitative objectives in concurrent and multiagent systems. Finally, we
consider the problem of computing outcomes that satisfy social welfare
constraints. To this end, we consider both utilitarian and egalitarian social
welfare and show that computing such outcomes is either PSPACE-complete or
NP-complete.
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