The knowledge-based software assistant

Where the Knowledge Based Software Assistant (KBSA) is now, four years after the initial report, is discussed. Also described is what the Rome Air Development Center expects at the end of the first contract iteration. What the second and third contract iterations will look like are characterized

The Knowledge-Based Software Assistant: Beyond CASE

This paper will outline the similarities and differences between two paradigms of software development. Both support the whole software life cycle and provide automation for most of the software development process, but have different approaches. The CASE approach is based on a set of tools linked by a central data repository. This tool-based approach is data driven and views software development as a series of sequential steps, each resulting in a product. The Knowledge-Based Software Assistant (KBSA) approach, a radical departure from existing software development practices, is knowledge driven and centers around a formalized software development process. KBSA views software development as an incremental, iterative, and evolutionary process with development occurring at the specification level

Creating and Capturing Artificial Emotions in Autonomous Robots and Software Agents

This paper presents ARTEMIS, a control system for autonomous robots or software agents. ARTEMIS is able to create and capture artificial emotions during interactions with its environment, and we describe the underlying mechanisms for this. The control system also realizes the capturing of knowledge about its past artificial emotions. A specific interpretation of a knowledge graph, called an Agent Knowledge Graph, represents these artificial emotions. For this, we devise a formalism which enriches the traditional factual knowledge in knowledge graphs with the representation of artificial emotions. As proof of concept, we realize a concrete software agent based on the ARTEMIS control system. This software agent acts as a user assistant and executes the user’s orders. The environment of this user assistant consists of autonomous service agents. The execution of user’s orders requires interaction with these autonomous service agents. These interactions lead to artificial emotions within the assistant. The first experiments show that it is possible to realize an autonomous agent with plausible artificial emotions with ARTEMIS and to record these artificial emotions in its Agent Knowledge Graph. In this way, autonomous agents based on ARTEMIS can capture essential knowledge that supports successful planning and decision making in complex dynamic environments and surpass emotionless agents

SMILE/ MARVEL: Two Approaches to Knowledge-Based Programming Environments

This technical report consists of three related papers in the area of intelligent assistance for software development and maintenance. Intelligent Assistance without Artificial Intelligence describes SMILE, a software engineering environment that assists teams of programmers without using AI technology. An Architecture for Intelligent Assistance in Software Development presents an AI approach to generalizing the capabilities of SMILE. Granularity Issues in a Knowledge-Based Programming Environment briefly describes MARVEL, an intelligent assistant based on this AI approach, and compares it to SMILE

Knowledge assistant: A sensor fusion framework for robotic environmental characterization

A prototype sensor fusion framework called the {open_quotes}Knowledge Assistant{close_quotes} has been developed and tested on a gantry robot at Sandia National Laboratories. This Knowledge Assistant guides the robot operator during the planning, execution, and post analysis stages of the characterization process. During the planning stage, the Knowledge Assistant suggests robot paths and speeds based on knowledge of sensors available and their physical characteristics. During execution, the Knowledge Assistant coordinates the collection of data through a data acquisition {open_quotes}specialist.{close_quotes} During execution and post analysis, the Knowledge Assistant sends raw data to other {open_quotes}specialists,{close_quotes} which include statistical pattern recognition software, a neural network, and model-based search software. After the specialists return their results, the Knowledge Assistant consolidates the information and returns a report to the robot control system where the sensed objects and their attributes (e.g. estimated dimensions, weight, material composition, etc.) are displayed in the world model. This paper highlights the major components of this system

Intelligent assistant to re-configure parameter-driven systems

Parameter-Driven Systems (PDS) are widely used in commerce for large-scale applications. Reusability is achieved with a PDS design by relocating implicit control structures in the software and the storage of explicit data in database files. This approach can accommodate various user requirements without tedious modification of the software. In order to specify appropriate parameters in a system, knowledge of both business activities and system behaviour are required. For large, complex software packages, this task becomes time consuming and requires specialist knowledge, yet the consistency and correctness still cannot be guaranteed. My research studied the types of knowledge required and agents involved in the PDS customisation. The work also identified the associated problems and constraints. A solution is proposed and implemented as an Intelligent Assistant prototype than a manual approach. Three areas of achievement have been highlighted: 1. The characteristics and problems of maintaining parameter instances in a PDS are defined. It is found that the verification is not complete with the technical/structural knowledge alone, but a context is necessary to provide semantic information and related business activities (thus the implemented parameters) so that mainline functions can relate with each other. 2. A knowledge-based modelling approach has been proposed and demonstrated via a practical implementation. A Specification Language was designed which can model various types of knowledge in a PDS and encapsulate relationships. The Knowledge-Based System (KBS) developed verifies parameters based on the interpreted model of a given context. 3. The performance of the Intelligent Assistant prototype was well received by the domain specialist from the participating organisation. The modelling and KBS approach developed in my research offers considerable promise in solving practical problems in the software industry

A knowledge representation semantic network for a natural language syntactic analyzer based on the UML

The need for improving software processes approximated the software engineering and artificial intelligence areas. Artificial intelligence techniques have been used as a support to software development processes, particularly through intelligent assistants that offer a knowledge-based support to software process’ activities. The context of the present work is a project for an intelligent assistant that implements a linguistic technique with the purpose of extracting object-oriented elements from requirement specifications in natural language through two main functionalities: the syntactic and semantic analyses. The syntactic analysis has the purpose of extracting the syntactic constituents from a sentence; and the semantic analysis has the goal of extracting the meaning from a set of sentences, i.e., a text. This paper focuses on the syntactic analysis functionality and applies the UML to its core as a semantic network for knowledge representation, based on the premise that the UML is de facto a standard general modeling language for software development.Applications in Artificial Intelligence - Language ProcessingRed de Universidades con Carreras en Informática (RedUNCI

An intelligent sales assistant for configurable products

Some of the recent proposals of web-based applications are oriented to provide advanced search services through virtual shops. Within this context, this paper proposes an advanced type of software application that simulates how a sales assistant dialogues with a consumer to dynamically configure a product according to particular needs. The paper presents the general knowl- edge model that uses artificial intelligence and knowledge-based techniques to simulate the configuration process. Finally, the paper illustrates the description with an example of an application in the field of photography equipment

An intelligent interface for satellite operations: Your Orbit Determination Assistant (YODA)

An intelligent interface is often characterized by the ability to adapt evaluation criteria as the environment and user goals change. Some factors that impact these adaptations are redefinition of task goals and, hence, user requirements; time criticality; and system status. To implement adaptations affected by these factors, a new set of capabilities must be incorporated into the human-computer interface design. These capabilities include: (1) dynamic update and removal of control states based on user inputs, (2) generation and removal of logical dependencies as change occurs, (3) uniform and smooth interfacing to numerous processes, databases, and expert systems, and (4) unobtrusive on-line assistance to users of concepts were applied and incorporated into a human-computer interface using artificial intelligence techniques to create a prototype expert system, Your Orbit Determination Assistant (YODA). YODA is a smart interface that supports, in real teime, orbit analysts who must determine the location of a satellite during the station acquisition phase of a mission. Also described is the integration of four knowledge sources required to support the orbit determination assistant: orbital mechanics, spacecraft specifications, characteristics of the mission support software, and orbit analyst experience. This initial effort is continuing with expansion of YODA's capabilities, including evaluation of results of the orbit determination task

Using an Ontology-based Approach to Build Open Assisting Tools in Foreign Language Writing

[EN] In today’s globalised world where there is a growing need for international communication, non-native speakers (NNS) from a wide range of professional fields are increasingly called upon to write specialised texts in English. More often than not, however, the linguistic competence required to do so is well beyond that of the majority of NNS. While software applications can serve to assist NNS in their English writing tasks, most of the applications available are designed for users of English for general purposes as opposed to English for professional purposes. Therefore, these applications lack the specific vocabulary, style guidelines and common structures required in more specialised documents. Necessary modifications to meet the needs of English for professional purposes tend to be viewed as representing an overly complex and expensive task. To overcome these challenges, we present a software called O-WEAA (Ontology-Writing English Assistant Architecture) which makes use of an ontology that represents the knowledge which, according to our formalisation, is required to write most types of specialised professional documents in the English language. Our formalisation of the required knowledge is based on an exhaustive linguistic analysis of several written genres. The proposed software is composed of two parts: i) a web application named Acquisition Interface Module, which allows experts to populate the ontology with new data and ii) a userfriendly, general web interface named Writing Assistant Interface Module which guides the user throughout the writing process of the English document in the specific domain described in the ontology.S