Search arXivSearch

arXiv · 0906.3119

Computational Power of P Systems with Small Size Insertion and Deletion Rules

Abstract

Recent investigations show insertion-deletion systems of small size that are not complete and cannot generate all recursively enumerable languages. However, if additional computational distribution mechanisms like P systems are added, then the computational completeness is achieved in some cases. In this article we take two insertion-deletion systems that are not computationally complete, consider them in the framework of P systems and show that the computational power is strictly increased by proving that any recursively enumerable language can be generated. At the end some open problems are presented.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Alexander Krassovitskiy, Yurii Rogozhin, Sergey Verlan. 2009-06-17. Computational Power of P Systems with Small Size Insertion and Deletion Rules. https://doi.org/10.4204/eptcs.1.10

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Graph Homomorphisms and Universal Algebra

Constraint satisfaction problems are computational problems that naturally appear in many areas of theoretical computer science. One of the central themes is their computational complexity, and in particular the border between polynomial-time tractability and NP-hardness. In this course we introduce the universal-algebraic approach to study the computational complexity of finite-domain CSPs. The course covers in particular the cyclic terms and bounded width theorems. To keep the presentation accessible, we start the course in the tangible setting of directed graphs and graph homomorphism problems.

cs.CC

The Exact Growth Rate of Space-Optimal Reversible Pebbling on Chains

We determine the exact time exponent of space-optimal reversible pebbling on chains as $1.331742379256310\ldots$. The growth rate of space-optimal reach exists as a limit and admits a variational formula. The same exponent governs complete computations at minimal space, uniformly in the chain length.

cs.CC

Randomized query complexity can beat certificate complexity

A long-standing open question in query complexity asks whether there is a total Boolean function f with R(f) << C(f), where R(f) and C(f) denote its bounded-error randomized query complexity and certificate complexity, respectively. We construct a function with R(f) = O~(sqrt{C(f)}), which is optimal up to log factors. The same function also has $Q(f) = O~(C(f)^{1/4}), where Q(f) is the bounded-error quantum query complexity of f, which is also nearly optimal.

cs.CC