On Measuring Non-Recursive Trade-Offs

We investigate the phenomenon of non-recursive trade-offs between descriptional systems in an abstract fashion. We aim at categorizing non-recursive trade-offs by bounds on their growth rate, and show how to deduce such bounds in general. We also identify criteria which, in the spirit of abstract language theory, allow us to deduce non-recursive tradeoffs from effective closure properties of language families on the one hand, and differences in the decidability status of basic decision problems on the other. We develop a qualitative classification of non-recursive trade-offs in order to obtain a better understanding of this very fundamental behaviour of descriptional systems

Computation with narrow CTCs

We examine some variants of computation with closed timelike curves (CTCs), where various restrictions are imposed on the memory of the computer, and the information carrying capacity and range of the CTC. We give full characterizations of the classes of languages recognized by polynomial time probabilistic and quantum computers that can send a single classical bit to their own past. Such narrow CTCs are demonstrated to add the power of limited nondeterminism to deterministic computers, and lead to exponential speedup in constant-space probabilistic and quantum computation. We show that, given a time machine with constant negative delay, one can implement CTC-based computations without the need to know about the runtime beforehand.Comment: 16 pages. A few typo was correcte

Context-dependent nondeterminism for pushdown automata

AbstractPushdown automata using a limited and unlimited amount of nondeterminism are investigated. Moreover, nondeterministic steps are allowed only within certain contexts, i.e., in configurations that meet particular conditions. The relationships of the accepted language families with closures of the deterministic context-free languages (DCFL) under regular operations are studied. For example, automata with unbounded nondeterminism that have to empty their pushdown store up to the initial symbol in order to make a guess are characterized by the regular closure of DCFL. Automata that additionally have to reenter the initial state are (almost) characterized by the Kleene star closure of the union closure of the prefix-free deterministic context-free languages. Pushdown automata with bounded nondeterminism are characterized by the union closure of DCFL in any of the considered contexts. Proper inclusions between all language classes discussed are shown. Finally, closure properties of these families under AFL operations are investigated

A Bit of Nondeterminism Makes Pushdown Automata Expressive and Succinct

We study the expressiveness and succinctness of good-for-games pushdown automata (GFG-PDA) over finite words, that is, pushdown automata whose nondeterminism can be resolved based on the run constructed so far, but independently of the remainder of the input word. We prove that GFG-PDA recognise more languages than deterministic PDA (DPDA) but not all context-free languages (CFL). This class is orthogonal to unambiguous CFL. We further show that GFG-PDA can be exponentially more succinct than DPDA, while PDA can be double-exponentially more succinct than GFG-PDA. We also study GFGness in visibly pushdown automata (VPA), which enjoy better closure properties than PDA, and for which we show GFGness to be EXPTIME-complete. GFG-VPA can be exponentially more succinct than deterministic VPA, while VPA can be exponentially more succinct than GFG-VPA. Both of these lower bounds are tight. Finally, we study the complexity of resolving nondeterminism in GFG-PDA. Every GFG-PDA has a positional resolver, a function that resolves nondeterminism and that is only dependant on the current configuration. Pushdown transducers are sufficient to implement the resolvers of GFG-VPA, but not those of GFG-PDA. GFG-PDA with finite-state resolvers are determinisable

Methods for Structural Pattern Recognition: Complexity and Applications

Katedra kybernetik

Beschreibungskomplexität von Zellularautomaten

Zellularautomaten sind ein massiv paralleles Berechnungsmodell, das aus sehr vielen identischen einfachen Prozessoren oder Zellen besteht, die homogen miteinander verbunden sind und parallel arbeiten. Es gibt Zellularautomaten in unterschiedlichen Ausprägungen. Beispielsweise unterscheidet man die Automaten nach der zur Verfügung stehenden Zeit, nach paralleler oder sequentieller Verarbeitung der Eingabe oder durch Beschränkungen der Kommunikation zwischen den einzelnen Zellen. Benutzt man Zellularautomaten zum Erkennen formaler Sprachen und betrachtet deren generative Mächtigkeit, dann kann bereits das einfachste zellulare Modell kontextsensitive Sprachen akzeptieren. In dieser Arbeit wird die Beschreibungskomplexität von Zellularautomaten betrachtet. Es wird untersucht, wie sich die Beschreibungsgröße einer formalen Sprache verändern kann, wenn die Sprache mit unterschiedlichen Typen von Zellularautomaten oder sequentiellen Modellen beschrieben wird. Ein wesentliches Ergebnis im ersten Teil der Arbeit ist, daß zwischen zwei Automatenklassen, deren entsprechende Sprachklassen echt ineinander enthalten oder unvergleichbar sind, nichtrekursive Tradeoffs existieren. Das heißt, der Größenzuwachs beim Wechsel von einem Automatenmodell in das andere läßt sich durch keine rekursive Funktion beschränken. Im zweiten Teil der Arbeit werden Zellularautomaten dahingehend beschränkt, daß nur eine feste Zellenzahl zugelassen ist. Zusätzlich werden Automaten mit unterschiedlichem Grad an bidirektionaler Kommunikation zwischen den einzelnen Zellen betrachtet, und es wird untersucht, welche Auswirkungen auf die Beschreibungsgröße unterschiedliche Grade an bidirektionaler Kommunikation haben können. Im Gegensatz zum unbeschränkten Modell können polynomielle und damit rekursive obere Schranken bei Umwandlungen zwischen den einzelnen Modellen bewiesen werden. Durch den Beweis unterer Schranken kann in fast allen Fällen auch die Optimalität der Konstruktionen belegt werden