On Maximally Parallel Schemata

A model for parallel computation called a schema is presented. This model is similar to that presented in the recent work of Karp and Miller. Section 1 presents a description of the model, and some results on the characterization of computations within it. Section 2 summarizes some results on determinacy and equivalence. Section 3 presents a formalization of the property of maximal parallelism in schemata. Several alternate characterizations are shown to be equivalent for certain classes. Section 4 presents results on the complexity of a maximally parallel schema equivalent to a given schema

On the Decomposition of Asynchronous Systems

This paper reports of part of a continuing investigation of parallel computation, in particular, efforts toward understanding the nature of different types of parallel control. The first section defines an asynchronous system to be a simple type of state machine. This was arrived at in an attempt to generalize from the types of control in parallel program schemata and networks of asynchronous modules without bounded delays. Asynchronous systems with output are also defined in a familiar way. The deviation from standard work comes in the definition of a parallel decomposition of asynchronous systems. Some preliminary work on compositions of this type appears in. Such definitions provide a useful analytic tool for discussion of related theories

Complexity Analysis of Precedence Terminating Infinite Graph Rewrite Systems

The general form of safe recursion (or ramified recurrence) can be expressed by an infinite graph rewrite system including unfolding graph rewrite rules introduced by Dal Lago, Martini and Zorzi, in which the size of every normal form by innermost rewriting is polynomially bounded. Every unfolding graph rewrite rule is precedence terminating in the sense of Middeldorp, Ohsaki and Zantema. Although precedence terminating infinite rewrite systems cover all the primitive recursive functions, in this paper we consider graph rewrite systems precedence terminating with argument separation, which form a subclass of precedence terminating graph rewrite systems. We show that for any precedence terminating infinite graph rewrite system G with a specific argument separation, both the runtime complexity of G and the size of every normal form in G can be polynomially bounded. As a corollary, we obtain an alternative proof of the original result by Dal Lago et al.Comment: In Proceedings TERMGRAPH 2014, arXiv:1505.06818. arXiv admin note: text overlap with arXiv:1404.619

Understanding and Cognitive Meaning: An Introduction

Meaning is wider in scope as well as more precious in value than is truth But even as respects truths meaning is the wider category truths are but one class of meanings namely those in which a claim to verifiability by their deduced empirical consequences is an intrinsic part of their validated meaning Beyond this island of meanings which in their own nature are true or false lies the ocean of meanings to which truth or falsity are irrelevan

Effects of the dominant in Secret Window.

This paper seeks to identify and examine 'problematic' aesthetic strategies in David Koepp's Secret Window (2004). Arguing that the film fits into a specific 'puzzle film' category favouring self-deceiving protagonists and surprise twists, the paper seeks to account for the negative critical reaction accrued by the film's denouement. Most centrally, I invoke the Russian Formalist's concept of the 'dominant' in order to suggest how Secret Window subordinates textual elements to the film's narrative revelation. It is this prioritising of the main plot twist that accounts for many of the film's dramaturgically contentious tactics. The paper demonstrates the means by which Secret Window cuts against the grain of Hollywood storytelling norms; it suggests that the film manipulates character engagement in a way that exceeds the puzzle film's traditional reshuffling of sympathies; and it indicates how the film deploys generic convention and allusion to engender a highly self-conscious and repressive narration. These arguments aim to show that the film displays bold and sophisticated aesthetic strategies. More broadly, the paper argues that by analysing problematic examples of a film genre, we can usefully disclose the aesthetic principles that underpin the genre's more successful films

Learning and memory in machines and animals : an AI model that accounts for some neurobiological data

The CEL model of learning and memory (Components of Episodic Learning) [Granger 1982, 1983a, 1983b] provides a process model of certain aspects of learning and memory in animals and humans. The model consists of a set of asynchronous and semi-independent functional operators that collectively create and modify memory traces as a result of experience. The model conforms to relevant results in the learning literature of psychology and neurobiology. There are two goals to this work: one is to create a set of working learning systems that will improve their performance on the basis of experience, and the other is to compare these systems' performance with that of living systems, as a step towards the eventual comparative characterizations of different learning systems.Parts of the model have been implemented in the CEL-0 program, which operates in a 'Maze-World' simulated maze environment. The program exhibits simple exploratory behavior that leads to the acquisition of predictive and discriminatory schemata. A number of interesting theoretical predictions have arisen in part from observation of the operation of the program, some of which are currently being tested in neurobiological experiments. In particular, some neurobiological evidence for the existence of multiple, seperable memory systems in humans and animals is interpreted in terms of the model, and some new experiments are suggested arising from the model's predictions

An integrated architecture for shallow and deep processing

We present an architecture for the integration of shallow and deep NLP components which is aimed at flexible combination of different language technologies for a range of practical current and future applications. In particular, we describe the integration of a high-level HPSG parsing system with different high-performance shallow components, ranging from named entity recognition to chunk parsing and shallow clause recognition. The NLP components enrich a representation of natural language text with layers of new XML meta-information using a single shared data structure, called the text chart. We describe details of the integration methods, and show how information extraction and language checking applications for realworld German text benefit from a deep grammatical analysis

SARDSRN: A NEURAL NETWORK SHIFT-REDUCE PARSER

Simple Recurrent Networks (SRNs) have been widely used in natural language tasks. SARDSRN extends the SRN by explicitly representing the input sequence in a SARDNET self-organizing map. The distributed SRN component leads to good generalization and robust cognitive properties, whereas the SARDNET map provides exact representations of the sentence constituents. This combination allows SARDSRN to learn to parse sentences with more complicated structure than can the SRN alone, and suggests that the approach could scale up to realistic natural language