Distributed Pushdown Automata Systems: Computational Power

2003 ◽  
pp. 218-229 ◽  
Author(s):  
Erzsébet Csuhaj-Varjú ◽  
Victor Mitrana ◽  
György Vaszil
Keyword(s):  
Computational Power ◽  
Pushdown Automata

scholarly journals On the computational power of pushdown automata

1970 ◽  
Vol 4 (2) ◽  
pp. 129-136 ◽  
Author(s):  
A.V. Aho ◽  
J.D. Ullman ◽  
J.E. Hopcroft
Keyword(s):  
Computational Power ◽  
Pushdown Automata

PARALLEL COMMUNICATING PUSHDOWN AUTOMATA SYSTEMS

2000 ◽  
Vol 11 (04) ◽  
pp. 631-650 ◽  
Author(s):  
ERZSÉBET CSUHAJ-VARJÚ ◽  
CARLOS MARTÍN-VIDE ◽  
VICTOR MITRANA ◽  
GYÖRGY VASZIL
Keyword(s):  
System Theory ◽  
Communication Strategy ◽  
Computational Power ◽  
Open Problems ◽  
Number Of Components ◽  
Grammar System ◽  
Bounded Number ◽  
Recursively Enumerable ◽  
Pushdown Automata ◽  
Recursively Enumerable Languages

We consider automata systems consisting of several pushdown automata working in parallel and communicating the contents of their stacks by request, using a communication strategy borrowed from grammar system theory. We investigate the computational power of these mechanisms. We prove that non-centralized parallel communicating pushdown automata systems with a bounded number of components, where each automaton is allowed to issue a query, are able to recognize all recursively enumerable languages. We also present homomorphical characterizations of the class of recursively enumerable languages for the centralized variants, where only a distinguished automaton issues queries. Moreover, we show that these centralized variants are at least as powerful as one-way multihead pushdown automata. Finally, some open problems and further directions of research are discussed.

Boosting Reversible Pushdown and Queue Machines by Preprocessing

2020 ◽  
pp. 1-29
Author(s):  
Holger Bock Axelsen ◽  
Martin Kutrib ◽  
Andreas Malcher ◽  
Matthias Wendlandt
Keyword(s):  
Real Time ◽  
Finite Automata ◽  
Point Of View ◽  
Regular Languages ◽  
Theoretical Point ◽  
Computational Power ◽  
Finite State ◽  
Finite State Transducer ◽  
Context Free ◽  
Pushdown Automata

It is well known that reversible finite automata do not accept all regular languages, that reversible pushdown automata do not accept all deterministic context-free languages, and that reversible queue automata are less powerful than deterministic real-time queue automata. It is of significant interest from both a practical and theoretical point of view to close these gaps. We here extend these reversible models by a preprocessing unit which is basically a reversible injective and length-preserving finite state transducer. It turns out that preprocessing the input using such weak devices increases the computational power of reversible deterministic finite automata to the acceptance of all regular languages, whereas for reversible pushdown automata the accepted family of languages lies strictly in between the reversible deterministic context-free languages and the real-time deterministic context-free languages. For reversible queue automata the preprocessing of the input leads to machines that are stronger than real-time reversible queue automata, but less powerful than real-time deterministic (irreversible) queue automata. Moreover, it is shown that the computational power of all three types of machines is not changed by allowing the preprocessing finite state transducer to work irreversibly. Finally, we examine the closure properties of the family of languages accepted by such machines.

scholarly journals Quantum Pushdown Automata with Garbage Tape

2018 ◽  
Vol 29 (03) ◽  
pp. 425-446 ◽  
Author(s):  
Masaki Nakanishi
Keyword(s):  
Impossibility Result ◽  
Computational Power ◽  
Pushdown Automaton ◽  
Proposed Model ◽  
Quantum Models ◽  
Pushdown Automata

Several kinds of quantum pushdown automata models have been proposed, and their computational power has been investigated intensively. However, for some quantum pushdown automaton models, it is unknown whether quantum models are at least as powerful as their classical counterparts or not. This is due to the reversibility restriction. In this paper, we introduce a new quantum pushdown automaton model that has a garbage tape. This model can overcome the reversibility restriction by exploiting the garbage tape to store popped symbols. We show that the proposed model can simulate any quantum pushdown automaton with classical stack as well as any probabilistic pushdown automaton. We also show that our model can solve a certain promise problem exactly while deterministic pushdown automata cannot. These results imply that our model is strictly more powerful than its classical counterparts in the setting of exact, one-sided error and non-deterministic computation. Showing impossibility for a promise problem is a difficult task in general. However, by analyzing the behavior of a deterministic pushdown automaton carefully, we obtained the impossibility result. This is one of the main contributions of the paper.

scholarly journals One-Time Nondeterministic Computations

2019 ◽  
Vol 30 (06n07) ◽  
pp. 1069-1089
Author(s):  
Markus Holzer ◽  
Martin Kutrib
Keyword(s):  
Finite Automata ◽  
State Machines ◽  
Computational Power ◽  
Deterministic Finite Automaton ◽  
Worst Case ◽  
Trade Offs ◽  
Finite State ◽  
Nondeterministic State ◽  
Pushdown Automata ◽  
Limited Nondeterminism

We introduce the concept of one-time nondeterminism as a new kind of limited nondeterminism for finite state machines and pushdown automata. Roughly speaking, one-time nondeterminism means that at the outset the computation is nondeterministic, but whenever it performs a guess, this guess is fixed for the rest of the computation. We characterize the computational power of one-time nondeterministic finite automata (OTNFAs) and one-time nondeterministic pushdown devices. Moreover, we study the descriptional complexity of these machines. For instance, we show that for an [Formula: see text]-state OTNFA with a sole nondeterministic state, that is nondeterministic for only one input symbol, [Formula: see text] states are sufficient and necessary in the worst case for an equivalent deterministic finite automaton. In case of pushdown automata, the conversion of a nondeterministic to a one-time nondeterministic as well as the conversion of a one-time nondeterministic to a deterministic one turn out to be non-recursive, that is, the trade-offs in size cannot be bounded by any recursive function.

Computational Power of Threshold Circuits of Energy at most Two

2018 ◽  
Vol E101.A (9) ◽  
pp. 1431-1439
Author(s):  
Hiroki MANIWA ◽  
Takayuki OKI ◽  
Akira SUZUKI ◽  
Kei UCHIZAWA ◽  
Xiao ZHOU
Keyword(s):  
Computational Power ◽  
Threshold Circuits

Current Scenario in Structure and Ligand-Based Drug Design on Anti-colon Cancer Drugs

2019 ◽  
Vol 24 (32) ◽  
pp. 3829-3841 ◽  
Author(s):  
Lakshmanan Loganathan ◽  
Karthikeyan Muthusamy
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Anticancer Agent ◽  
Computational Power ◽  
Cancer Drugs ◽  
Recent Advances ◽  
Anti Cancer ◽  
Drug Designing ◽  
Current Scenario ◽  
Molecular Modeling Studies

Worldwide, colorectal cancer takes up the third position in commonly detected cancer and fourth in cancer mortality. Recent progress in molecular modeling studies has led to significant success in drug discovery using structure and ligand-based methods. This study highlights aspects of the anticancer drug design. The structure and ligand-based drug design are discussed to investigate the molecular and quantum mechanics in anti-cancer drugs. Recent advances in anticancer agent identification driven by structural and molecular insights are presented. As a result, the recent advances in the field and the current scenario in drug designing of cancer drugs are discussed. This review provides information on how cancer drugs were formulated and identified using computational power by the drug discovery society.

A Human/Computer Learning Network to Improve Biodiversity Conservation and Research

AI Magazine ◽  
2012 ◽  
Vol 34 (1) ◽  
pp. 10 ◽  
Author(s):  
Steve Kelling ◽  
Jeff Gerbracht ◽  
Daniel Fink ◽  
Carl Lagoze ◽  
Weng-Keen Wong ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Feedback Loop ◽  
Human Computation ◽  
Computational Power ◽  
Learning Networks ◽  
Learning Network ◽  
Computer Learning ◽  
The Individual ◽  
Citizen Science Project

In this paper we describe eBird, a citizen-science project that takes advantage of the human observational capacity to identify birds to species, which is then used to accurately represent patterns of bird occurrences across broad spatial and temporal extents. eBird employs artificial intelligence techniques such as machine learning to improve data quality by taking advantage of the synergies between human computation and mechanical computation. We call this a Human-Computer Learning Network, whose core is an active learning feedback loop between humans and machines that dramatically improves the quality of both, and thereby continually improves the effectiveness of the network as a whole. In this paper we explore how Human-Computer Learning Networks can leverage the contributions of a broad recruitment of human observers and processes their contributed data with Artificial Intelligence algorithms leading to a computational power that far exceeds the sum of the individual parts.

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