1,596 research outputs found
The Complexity of Reasoning for Fragments of Autoepistemic Logic
Autoepistemic logic extends propositional logic by the modal operator L. A
formula that is preceded by an L is said to be "believed". The logic was
introduced by Moore 1985 for modeling an ideally rational agent's behavior and
reasoning about his own beliefs. In this paper we analyze all Boolean fragments
of autoepistemic logic with respect to the computational complexity of the
three most common decision problems expansion existence, brave reasoning and
cautious reasoning. As a second contribution we classify the computational
complexity of counting the number of stable expansions of a given knowledge
base. To the best of our knowledge this is the first paper analyzing the
counting problem for autoepistemic logic
Graph- versus Vector-Based Analysis of a Consensus Protocol
The Paxos distributed consensus algorithm is a challenging case-study for
standard, vector-based model checking techniques. Due to asynchronous
communication, exhaustive analysis may generate very large state spaces already
for small model instances. In this paper, we show the advantages of graph
transformation as an alternative modelling technique. We model Paxos in a rich
declarative transformation language, featuring (among other things) nested
quantifiers, and we validate our model using the GROOVE model checker, a
graph-based tool that exploits isomorphism as a natural way to prune the state
space via symmetry reductions. We compare the results with those obtained by
the standard model checker Spin on the basis of a vector-based encoding of the
algorithm.Comment: In Proceedings GRAPHITE 2014, arXiv:1407.767
Quantum strategies
We consider game theory from the perspective of quantum algorithms.
Strategies in classical game theory are either pure (deterministic) or mixed
(probabilistic). We introduce these basic ideas in the context of a simple
example, closely related to the traditional Matching Pennies game. While not
every two-person zero-sum finite game has an equilibrium in the set of pure
strategies, von Neumann showed that there is always an equilibrium at which
each player follows a mixed strategy. A mixed strategy deviating from the
equilibrium strategy cannot increase a player's expected payoff. We show,
however, that in our example a player who implements a quantum strategy can
increase his expected payoff, and explain the relation to efficient quantum
algorithms. We prove that in general a quantum strategy is always at least as
good as a classical one, and furthermore that when both players use quantum
strategies there need not be any equilibrium, but if both are allowed mixed
quantum strategies there must be.Comment: 8 pages, plain TeX, 1 figur
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