Abstract
This work aims at improving the scalability of memory usage in Inductive Logic Programming systems. In this context, we propose two efficient data structures: the Trie, used to represent lists and clauses; and the RL-Tree, a novel data structure used to represent the clauses coverage. We evaluate their performance in the April system using well known datasets. Initial results show a substantial reduction in memory usage without incurring extra execution time overheads. Our proposal is applicable in any ILP system.

Abstract
The lack of dynamic double-side regulation models for E-Marketplaces is a main reason for their lack of success as advanced open trading places.In this paper, a new model - DYNEX - is developed to generate homogeneous markets of goods or services and to optimize for each homogeneous market the trading price and the negotiation process between buyers and sellers.

Abstract
This paper presents a new Web-based system, Mooshak, to handle programming contests. The system acts as a full contest manager as well as an automatic judge for programming contests. Mooshak innovates in a number of aspects: it has a scalable architecture that can be used from small single server contests to complex multi-site contests with simultaneous public online contests and redundancy; it has a robust data management system favoring simple procedures for storing, replicating, backing up data and failure recovery using persistent objects; it has automatic judging capabilities to assist human judges in the evaluation of programs; it has built-in safety measures to prevent users from interfering with the normal progress of contests. Mooshak is an open system implemented on the Linux operating system using the Apache HTTP server and the TcI scripting language. This paper starts by describing the main features of the system and its architecture with reference to the automated judging, data management based on the replication of persistent objects over a network. Finally, we describe our experience using this system for managing two official programming contests. Copyright (C) 2003 John Wiley Sons, Ltd.

Abstract
This paper compares the performance of classical position PD algorithm with a cascade controller involving position and force feedback loops, for multi-legged locomotion systems and variable ground characteristics. For that objective the robot prescribed motion is characterized in terms of several locomotion variables. Moreover, we formulate several performance measures of the walking robot based on the robot and terrain dynamical properties and on the robot hip and foot trajectory errors. Several experiments reveal the performance of the different control architectures in the proposed indices.

Abstract
It is known that there is a class of nonlinear systems that cannot be stabilized by a continuous time-invariant feedback. This class includes systems with interest in practice, such as nonholonomic systems, frequently appearing in robotics and other areas. Yet, most continuous-time model predictive control (MPC) frameworks had to assume continuity of the resulting feedback law, being unable to address an important class of nonlinear systems. It is also known that the open-loop optimal control problems that are solved in MPC algorithms may not have, in general, a continuous solution. Again, most continuous-time MPC frameworks had to artificially assume continuity of the optimal controls or, alternatively, impose some demanding assumptions on the data of the optimal control problem to achieve the desired continuity. In this work we analyse the reasons why traditional MPC approaches had to impose the continuity assumptions, the difficulties in relaxing these assumptions, and how the concept of 'sampling feedbacks' combines naturally with MPC to overcome these difficulties. A continuous-time MPC framework using a strictly positive inter-sampling time is argued to be appropriate to use with discontinuous optimal controls and discontinuous feedbacks. The essential features for the stability of such MPC framework are reviewed. Copyright (C) 2003 John Wiley Sons, Ltd.

Abstract
This paper analyzes the performance of a hexapod robot under the action of a cascade controller involving position and force feedback loops. In order to evaluate the system properties we formulate several measures of the walking system based on the system dynamics and the trajectory errors. Simulation experiments reveal the influence of the different control algorithms upon the proposed indices.