A Domain-Independent Algorithm for Plan Adaptation

The paradigms of transformational planning, case-based planning, and plan debugging all involve a process known as plan adaptation - modifying or repairing an old plan so it solves a new problem. In this paper we provide a domain-independent algorithm for plan adaptation, demonstrate that it is sound, complete, and systematic, and compare it to other adaptation algorithms in the literature. Our approach is based on a view of planning as searching a graph of partial plans. Generative planning starts at the graph's root and moves from node to node using plan-refinement operators. In planning by adaptation, a library plan - an arbitrary node in the plan graph - is the starting point for the search, and the plan-adaptation algorithm can apply both the same refinement operators available to a generative planner and can also retract constraints and steps from the plan. Our algorithm's completeness ensures that the adaptation algorithm will eventually search the entire graph and its systematicity ensures that it will do so without redundantly searching any parts of the graph.Comment: See http://www.jair.org/ for any accompanying file

Modeling the Pāṇinian System of Sanskrit Grammar

The present work is a study of the Aṣṭādhyāyī of Pāṇini from a new perspective. It attempts to explore the Pāṇinian system of Sanskrit grammar from a formal point of view and investigate the possibilities of representing it in a logical, explicit and consistent manner. It puts forward an appropriate framework for such a representation. Differing from the formulation of Aṣṭādhyāyī, which is composed in an artificial yet natural language and is meant to be employed by individuals who are acquainted both with the Sanskrit language and the techniques of grammar, the present rendering aims for a non-verbal representation in terms of mathematical categories and logical relations which can be implemented in an algorithmic manner. The formal framework suggested in this work would facilitate adequate tools for postulating and evaluating hypotheses about the grammatical system. Moreover, it would furnish the basis for a computer implementation of the grammar. Both these aspects are objects of enquiry in the field of theoretical studies on Pāṇini as well as the emerging discipline of Sanskrit computational linguistics. This book takes on the ground-work in these areas.Die vorliegende Arbeit untersucht aus einer neuen Perspektive Pāṇinis Aṣṭādhyāyī. Es versucht, Pāṇinis Regelwerk der Sanskrit-Grammatik aus formaler Sicht zu erforschen und die Möglichkeiten zu untersuchen, es logisch, explizit und konsistent darzustellen. Dazu wird ein geeignetes Framework für eine solche Repräsentation vorgeschlagen. Im Unterschied zur Aṣṭādhyāyī, die in einer künstlichen, aber natürlichen Sprache verfasst ist und für Personen konzipiert war, die sowohl mit der Sanskrit-Sprache als auch mit grammatischen Techniken vertraut sind, zielt die vorliegende Darstellung auf eine nonverbale Repräsentation in Form von mathematischen Kategorien und logischen Beziehungen ab, die algorithmisch umgesetzt werden können. Der in dieser Arbeit vorgeschlagene formale Rahmen würde geeignete Werkzeuge bereitstellen, um Hypothesen zum grammatischen System zu postulieren und zu evaluieren. Darüber hinaus würde er die Grundlage für eine computergestützte Implementierung der Grammatik schaffen. Beide Aspekte sind Forschungsgegenstand im Bereich der theoretischen Studien zu Pāṇini sowie der neu entstehenden Disziplin der Sanskrit-Computerlinguistik. Dieses Buch beschäftigt sich mit der Grundlagenarbeit in diesen Bereichen

QuickAssist Extensive Reading for Learners of German Using CALL Technologies

The focus of this dissertation is the development and testing of a CALL tool which assists learners of German with the extensive reading of German texts of their choice. The application provides functionality that enables learners to acquire new vocabulary, analyse the meaning of complex word forms and to study a word’s semantic and syntactic features with the help of corpora and online resources. It is also designed to enable instructors to create meaningful exercises to be used in classroom activities focusing on vocabulary acquisition and word formation rules. The detailed description of the software development and implementation is preceded by a review of the relevant literature in the areas of German morphology and word formation, second language acquisition and vocabulary acquisition in particular, studies on the benefits of extensive reading, the role of motivation in second language learning, CALL, and natural language processing technologies. The user study presented at the end of this dissertation shows how a first test group of learners was able to use the application for individual reading projects and presents the results of an evaluation of the software conducted by three German instructors assessing the affordances of the applications for students and potential applications for language instructors

Exploiting More Binaries by Using Planning to Assemble ROP Attacks

Return oriented programming (ROP) attacks have been studied for many years, but they are usually still constructed manually. The existing tools to synthesize ROP exploits automatically, such as ROPGadget and angrop, are very limited by their ad-hoc design: they rely on matching fixed patterns and assembling gadgets in fixed ways. We propose a new method, PEACE, that uses symbolic execution and partial-order planning to assemble gadgets more flexibly. Our method incrementally selects gadgets to address a need in the partially-constructed exploit, and infers ordering constraints over those gadgets based on their effects. This approach enables PEACE to create exploits for many more binaries than existing tools. By creating a more flexible and powerful ROP attack generation tool, we hope to raise awareness of how much code is vulnerabl

Transformational maintenance by reuse of design histories

This thesis provides theory and procedures for modifying software artifacts implemented by a formal transformation process. Installing modifications requires knowing not only what transformations were applied (a derivation history) to construct the artifact, but also why the application sequence ensures that the artifact meets its specification. The derivation history and the justification are collectively called a design history. A Design Maintenance System (DMS), when provided with a formal change called a maintenance delta, revises a design history to guide construction of a new artifact. A DMS can be used to integrate a stream of deltas into a history, providing implementations as a side effect, leading to an incremental-evolution model for software construction.We provide a broadly applicable formal model of transformation systems in which specifications are performance predicates, subsuming the functional specifications which are traditional for transformation systems. Such performance predicates provide vocabulary used in the design history to describe the effect of applying sets of transformations.A nonprocedural, performance-goal-oriented Transformation Control Language (TCL) is defined to control navigation of the design space for a transformation system. Recording the execution of a TCL metaprogram directly provides a design history.A complete classification of, and representation for, the set of possible maintenance deltas is given in terms of the inputs defined by the transformation system model. Such deltas include not only specification changes, but also changes to implementation support technologies. Delta integration procedures for revising derivation histories given functional or support technology deltas are provided, based on rearranging the order of transformations in the design space. Building on these operations, integration procedures that revise the design history for each type of delta are described. An agenda-oriented TCL execution process dovetails smoothly with the integration procedures.Our DMS is compared to a number of other maintenance systems. By using an explicit delta and verified commutativity, our DMS often reuses transformations correctly when others fail

Computer tool for use by children with learning difficulties in spelling

The development of a computer tool to be used by children with learning difficulties in spelling is described in this thesis. Children with spelling disabilities were observed by the author, and their errors were recorded. Based on analysis of these errors, a scheme of error classification was devised. It was hypothesized that there were regularities in the errors; that the classification scheme describing these errors could provide adequate information to enable a computer program to 'debug' the children's errors and to reconstruct the intended words; and that the children would be able to recognize correct spellings even if they could not produce them. Two computer programs, the EDITCOST and the PHONCODE programs, were developed. These incorporated information about the types of errors that were made by the children, described in terms of the classification scheme. They were used both to test the hypotheses and as potential components of a larger program to be used as a compensatory tool. The main conclusions drawn from this research are: The errors made by children with learning difficulties in spelling show regularities in both the phoneme-grapheme correspondences and at the level of the orthography. The classification scheme developed, based on the children's errors, provides a description of these errors. It provides adequate information to enable a computer program to 'debug' the children's errors and to reconstruct the intended words. Computer tools in the form of interactive spelling correctors are able to offer a correction for a substantial proportion of the child's errors, and could be extended to provide more information about the children's errors. They are also suitable for use with other groups of children

Synthesis of Strategies for Non-Zero-Sum Repeated Games

There are numerous applications that involve two or more self-interested autonomous agents that repeatedly interact with each other in order to achieve a goal or maximize their utilities. This dissertation focuses on the problem of how to identify and exploit useful structures in agents' behavior for the construction of good strategies for agents in multi-agent environments, particularly non-zero-sum repeated games. This dissertation makes four contributions to the study of this problem. First, this thesis describes a way to take a set of interaction traces produced by different pairs of players in a two-player repeated game, and then find the best way to combine them into a strategy. The strategy can then be incorporated into an existing agent, as an enhancement of the agent's original strategy. In cross-validated experiments involving 126 agents for the Iterated Prisoner's Dilemma, Iterated Chicken Game, and Iterated Battle of the Sexes, my technique was able to make improvement to the performance of nearly all of the agents. Second, this thesis investigates the issue of uncertainty about goals when a goal-based agent situated in a nondeterministic environment. The results of this investigation include the necessary and sufficiency conditions for such guarantee, and an algorithm for synthesizing a strategy from interaction traces that maximizes the probability of success of an agent even when no strategy can assure the success of the agent. Third, this thesis introduces a technique, Symbolic Noise Detection (SND), for detecting noise (i.e., mistakes or miscommunications) among agents in repeated games. The idea is that if we can build a model of the other agent's behavior, we can use this model to detect and correct actions that have been affected by noise. In the 20th Anniversary Iterated Prisoner's Dilemma competition, the SND agent placed third in the "noise" category, and was the best performer among programs that had no "slave" programs feeding points to them. Fourth, the thesis presents a generalization of SND that can be wrapped around any existing strategy. Finally, the thesis includes a general framework for synthesizing strategies from experience for repeated games in both noisy and noisy-free environments

Neural Semantic Parsing for Syntax-Aware Code Generation

The task of mapping natural language expressions to logical forms is referred to as semantic parsing. The syntax of logical forms that are based on programming or query languages, such as Python or SQL, is defined by a formal grammar. In this thesis, we present an efficient neural semantic parser that exploits the underlying grammar of logical forms to enforce well-formed expressions. We use an encoder-decoder model for sequence prediction. Syntactically valid programs are guaranteed by means of a bottom-up shift-reduce parser, that keeps track of the set of viable tokens at each decoding step. We show that the proposed model outperforms the standard encoder-decoder model across datasets and is competitive with comparable grammar-guided semantic parsing approaches