Constantine Halatsis

eg-GRIDS: Context-Free Grammatical Inference from Positive Examples Using Genetic Search

In this paper we present eg-GRIDS, an algorithm for inducing context-free grammars that is able to learn from positive sample sentences. The presented algorithm, similar to its GRIDS predecessors, uses simplicity as a criterion for directing inference, and a set of operators for exploring the search space. In addition to the basic beam search strategy of GRIDS, eg-GRIDS incorporates an evolutionary grammar selection process, aiming to explore a larger part of the search space. Evaluation results are presented on artificially generated data, comparing the performance of beam search and genetic search. These results show that genetic search performs better than beam search while being significantly more efficient computationally.

e-Learning Issues under an Affective Perspective

The aim of this paper is to present an Affective Educational Module for distance learning which is called MENTOR. MENTOR constitutes of three main components, the Emotional Component, the Teacher Component and the Visualization Component and its main purpose is to motivate appropriately the student in order to accomplish his learning goals. The basic concern of MENTOR is to retain the students emotional state positive during the learning process. To achieve this, it recognizes the emotions of the students and takes them under consideration to provide them with the suitable learning strategy. This kind of strategy is based both on the cognitive abilities and the affective preferences of the student and is stored in the students model. The student model supplies the educational system with necessary information with the aim to adapt itself successfully to the students needs.

PETINA—tour generation using the ElipSys inference system

PETINA is a Personalized Tourist Information Advisor system aiming at helping tourists to construct tours satisfying specified constraints. The system consults a large database that contains tourist data. PETINA has been implemented in the ElipSys language, which is a pure parallel logic programming system extended with various powerful mechanisms and features to allow efficient parallel execution. Although the expressive power of logic programming is profitable for the development of PETINA, standard Prolog systems lack of facilities that are vital for the PETINA application to work. ElipSys haa proved to be very suitable tool for the implementation of PETINA, as most of the former’s features are indispensable for handling the complexity of the encountered problems.

MaDCoWS: A Scalable Distributed Shared Memory Environment for Massively Parallel Multiprocessors

In this paper we present MaDCoWS, a software implementation of a Distributed Shared Memory (DSM) runtime system, specifically designed for massively parallel 2-D grid multiprocessors. The system takes advantage of the network topology in order to minimise the paths of the message sequences realising the shared operations. As a result its performance is increased and the system becomes scalable even to very large processor numbers. We present the basic ideas for 2-D optimisations, the implementation structure and results from synthetic and application benchmarks executed on a 1024 processor Parsytec GCel.

Predictive Automated Negotiators Employing Risk-Seeking and Risk-Averse Strategies

Intelligent agents that seek to automate various stages of the negotiation process are often enhanced with models of computational intelligence extending the cognitive abilities of the parties they represent. This paper is focused on predictive strategies employed by automated negotiators, and particularly those based on forecasting the counterpart’s responses. In this context a strategy supporting negotiations over multiple issues is presented and assessed. Various behaviors emerge with respect to negotiator’s attitude towards risk, resulting to different utility gains. Forecasting is conducted with the use of Multilayer Perceptrons (MLPs) and the training set is extracted online during the negotiation session. Two cases are examined: in the first separate MLPs are used for the estimations of each negotiable attribute, whereas in the second a single MLP is used to estimate the counterpart’s response. Experiments are conducted to search the architecture of the MLPs.

Improving the Performance of Distributed Shared Memory Environments on Grid Multiprocessors

Distributed Shared Memory (DSM) is a good solution to the scalability, complexity and high cost problems of large scale Shared Memory Multiprocessors, as well as to the difficulty of the programming model problem of the message passing Distributed Memory Multiprocessors. We present a method for improving the performance of Distributed Shared Memory Environments running on grid multiprocessors. The method is based on removing the inherent centralism imposed by X-Y routing that causes congestion in the centre of the grid Simulation, as well as implementation results on a 1024 processor machine show an improvement of up to 24%.

A multimedia title development environment (MTDE)

Abstract The development of Multimedia Titles (M-Titles) (i.e., multimedia applications stored on CDs) is performed by many designers and implementors using tools that run on specific platforms and often have complementary and/or overlapping functionality. The potential designer or implementor of an M-Title is restricted by the availability of tools on a selected development platform. This paper presents a Multimedia Title Development Environment (MTDE), which integrates multimedia information, tools used to produce it, as well as their formats and storage media as objects in an Asset Repository. The cooperative construction of complex multimedia objects is modelled as a DAG consisting of two types of nodes: multimedia objects and actions applied to multimedia objects. An M-Title consists of a number of complex multimedia objects linked with each other in a hypernetwork of relationships. MTDE enables a group of authors to cooperatively construct M-Titles as a hypernetwork of multimedia nodes by activating tools running on various platforms, by exploiting the hypermedia functionality of MTDE, and by reusing existing material from the Asset Repository.