Abstract
Set plays are predefined collaborative coordinate actions that players from any sport can use to gain advantage over its adversaries. Recently, a complete framework for creation and execution of this kind of coordinate behavior by teams composed of multiple independent agents was launched as free software (the Set play Framework). In this paper, an approach based on Reinforcement Learning(RL) is proposed, that allows the use of experience to devise the better course of action in set plays with multiple choices. Simulations results show that the proposed approach allows a team of simulated agents to improve its performance against a known adversary team, achieving better results than previously proposed approaches using RL.

Abstract

Abstract

Abstract
Enterprise Service Bus (ESB) is a middleware infrastructure that provides a way to integrate loosely-coupled heterogeneous software applications based on the services principles. The life-cycle management of services in such environments is a critical issue for the component's reuse, maintenance and operation. This paper introduces a service life-cycle management module that extends the traditional functionalities with advanced monitoring and data analytics to contribute for the robustness, reliability and self-organization of networks of clusters based on ESB platforms. The realization of this module was embedded in the JBoss ESB, considering a sniffer mechanism to collect the service messages crossing the bus and a Liferay portal to display relevant information related to the services' health. © 2014 IEEE.

Abstract
The traditional approach for specifying adaptive behavior in embedded applications requires developers to engage in error-prone programming tasks. This results in long design cycles and in the inherent inability to explore and evaluate a wide variety of alternative adaptation behaviors, critical for systems exposed to dynamic operational and situational environments. In this paper, we introduce a domain-specific language (DSL) for specifying and implementing run-time adaptable application behavior. We illustrate our approach using a real-life stereo navigation application as a case study, highlighting the impact and benefits of dynamically adapting algorithm parameters. The experiments reveal our approach effective, as such run-time adaptations are easily specified in a higher level by the DSL, and thus at a lower programming effort than when using a general-purpose language such as C.

Abstract
As a complex artefact, software has to meet requirements formulated and verified at different levels of abstraction. A basic distinction is drawn between behavioural (dynamic) and data (static) aspects. From an educational point of view, although disguised under a number of different designations, both issues are usually present, but kept separated, in typical Computer Science undergraduate curricula. It is often argued that they tackle orthogonal problems through essentially different methods. This paper explores an alternative path in which students progress from equational to hybrid specifications in a uniform setting, integrating paradigms, combining data and behaviour, and dealing appropriately with systems evolution and reconfiguration.