An integrated theory of language production and comprehension

Currently, production and comprehension are regarded as quite distinct in accounts of language processing. In rejecting this dichotomy, we instead assert that producing and understanding are interwoven, and that this interweaving is what enables people to predict themselves and each other. We start by noting that production and comprehension are forms of action and action perception. We then consider the evidence for interweaving in action, action perception, and joint action, and explain such evidence in terms of prediction. Specifically, we assume that actors construct forward models of their actions before they execute those actions, and that perceivers of others' actions covertly imitate those actions, then construct forward models of those actions. We use these accounts of action, action perception, and joint action to develop accounts of production, comprehension, and interactive language. Importantly, they incorporate well-defined levels of linguistic representation (such as semantics, syntax, and phonology). We show (a) how speakers and comprehenders use covert imitation and forward modeling to make predictions at these levels of representation, (b) how they interweave production and comprehension processes, and (c) how they use these predictions to monitor the upcoming utterances. We show how these accounts explain a range of behavioral and neuroscientific data on language processing and discuss some of the implications of our proposal

Towards a complete multiple-mechanism account of predictive language processing [Commentary on Pickering & Garrod]

Although we agree with Pickering & Garrod (P&G) that prediction-by-simulation and prediction-by-association are important mechanisms of anticipatory language processing, this commentary suggests that they: (1) overlook other potential mechanisms that might underlie prediction in language processing, (2) overestimate the importance of prediction-by-association in early childhood, and (3) underestimate the complexity and significance of several factors that might mediate prediction during language processing

Flexibly Instructable Agents

This paper presents an approach to learning from situated, interactive tutorial instruction within an ongoing agent. Tutorial instruction is a flexible (and thus powerful) paradigm for teaching tasks because it allows an instructor to communicate whatever types of knowledge an agent might need in whatever situations might arise. To support this flexibility, however, the agent must be able to learn multiple kinds of knowledge from a broad range of instructional interactions. Our approach, called situated explanation, achieves such learning through a combination of analytic and inductive techniques. It combines a form of explanation-based learning that is situated for each instruction with a full suite of contextually guided responses to incomplete explanations. The approach is implemented in an agent called Instructo-Soar that learns hierarchies of new tasks and other domain knowledge from interactive natural language instructions. Instructo-Soar meets three key requirements of flexible instructability that distinguish it from previous systems: (1) it can take known or unknown commands at any instruction point; (2) it can handle instructions that apply to either its current situation or to a hypothetical situation specified in language (as in, for instance, conditional instructions); and (3) it can learn, from instructions, each class of knowledge it uses to perform tasks.Comment: See http://www.jair.org/ for any accompanying file

Requirements analysis of the VoD application using the tools in TRADE

This report contains a specification of requirements for a video-on-demand (VoD) application developed at Belgacom, used as a trial application in the 2RARE project. The specification contains three parts: an informal specification in natural language; a semiformal specification consisting of a number of diagrams intended to illustrate the informal specification; and a formal specification that makes the requiremants on the desired software system precise. The informal specification is structured in such a way that it resembles official specification documents conforming to standards such as that of IEEE or ESA. The semiformal specification uses some of the tools in from a requirements engineering toolkit called TRADE (Toolkit for Requirements And Design Engineering). The purpose of TRADE is to combine the best ideas in current structured and object-oriented analysis and design methods within a traditional systems engineering framework. In the case of the VoD system, the systems engineering framework is useful because it provides techniques for allocation and flowdown of system functions to components. TRADE consists of semiformal techniques taken from structured and object-oriented analysis as well as a formal specification langyage, which provides constructs that correspond to the semiformal constructs. The formal specification used in TRADE is LCM (Language for Conceptual Modeling), which is a syntactically sugared version of order-sorted dynamic logic with equality. The purpose of this report is to illustrate and validate the TRADE/LCM approach in the specification of distributed, communication-intensive systems

Transformation reborn: A new generation expert system for planning HST operations

The Transformation expert system (TRANS) converts proposals for astronomical observations with the Hubble Space Telescope (HST) into detailed observing plans. It encodes expert knowledge to solve problems faced in planning and commanding HST observations to enable their processing by the Science Operations Ground System (SOGS). Among these problems are determining an acceptable order of executing observations, grouping of observations to enhance efficiency and schedulability, inserting extra observations when necessary, and providing parameters for commanding HST instruments. TRANS is currently an operational system and plays a critical role in the HST ground system. It was originally designed using forward-chaining provided by the OPS5 expert system language, but has been reimplemented using a procedural knowledge base. This reimplementation was forced by the explosion in the amount of OPS5 code required to specify the increasingly complicated situations requiring expert-level intervention by the TRANS knowledge base. This problem was compounded by the difficulty of avoiding unintended interaction between rules. To support the TRANS knowledge base, XCL, a small but powerful extension to Commom Lisp was implemented. XCL allows a compact syntax for specifying assignments and references to object attributes. XCL also allows the capability to iterate over objects and perform keyed lookup. The reimplementation of TRANS has greatly diminished the effort needed to maintain and enhance it. As a result of this, its functions have been expanded to include warnings about observations that are difficult or impossible to schedule or command, providing data to aid SPIKE, an intelligent planning system used for HST long-term scheduling, and providing information to the Guide Star Selection System (GSSS) to aid in determination of the long range availability of guide stars

A Proposal for Semantic Map Representation and Evaluation

Semantic mapping is the incremental process of “mapping” relevant information of the world (i.e., spatial information, temporal events, agents and actions) to a formal description supported by a reasoning engine. Current research focuses on learning the semantic of environments based on their spatial location, geometry and appearance. Many methods to tackle this problem have been proposed, but the lack of a uniform representation, as well as standard benchmarking suites, prevents their direct comparison. In this paper, we propose a standardization in the representation of semantic maps, by defining an easily extensible formalism to be used on top of metric maps of the environments. Based on this, we describe the procedure to build a dataset (based on real sensor data) for benchmarking semantic mapping techniques, also hypothesizing some possible evaluation metrics. Nevertheless, by providing a tool for the construction of a semantic map ground truth, we aim at the contribution of the scientific community in acquiring data for populating the dataset

English as common legal language: Its expansion and the effects on civil law and common law lawyers

English has become the common language in a globalized legal world. However, the far-reaching consequences of the domination of key areas of the international practice of law by legal English are not yet fully understood and analysed. This article is concerned with an analysis of the expansion of legal English in global legal practice. This area has also been described as the ‘Law Market’, i.e. the area of activities of global lawyers in coping with the regulatory and legal frameworks in which international businesses function.’2 Much of the existing research into legal English as a common language is concerned with the development of legal English as a vehicle language for non-native English speakers in the sense of a lingua franca.3 The discussion is divided into either promoting the use of legal English as global language4 or pointing to its limitations ‘in that its legal terminology is premised on the tools of the (minority) common law system’5. This article aims to assess the interface and dynamics between lawyers using legal English as a common language as well as foreign languages in their legal work. This includes lawyers trained in the common law and/or civil law. Its aim is to gain a better understanding of global lawyering and communication in law and business relationships and to develop strategies for the internationalization of legal education and training in the UK