This paper presents a description of the environments of individualized learning (Based on the Intelligent Tutoring Systems, ITS), the Computer Supported Collaborative Learning (CSCL), Multi-Agent Systems (MAS) and the artificial intelligence techniques called: Instructional Planning (IP) and Case-Based Reasoning (CBR). Finally ALLEGRO is presented, a MAS environment of support to the teaching/...

Multi Agent Systems (MAS) comprise of a collection of autonomous and interacting agents that adapt to their environment. The agents within a MAS exhibit many of the same behaviours in the form of cross-cutting concerns. Aspects are a technology that can be used to represent cross-cutting concerns by weaving them through a system at specific points. In this paper a development process based on t...

Multi-Agent Systems (MAS) promise a new advance in distributed computing. In MAS autonomous software agents flexibly cooperate, coordinate and compete to provide the desired function(s) of such a system. If some components of a MAS fail or do not provide the desired functionality, the system is expected to autonomously deal with this situation. It is desirable to reduce occurrences of such situ...

The era of distributed software environments is emerging and research on multi-agent systems (MAS), which tries to solve complex problems using entities called agents, is on the rise. This paper proposes an architecture-centric method for developing MAS that supports the important phases of systematic software development. In particular, this approach is geared towards supporting system propert...

Stability is perhaps the most desired feature in the systems that we design. It is important for us to be able to predict the response of a Multi-Agent System (MAS) to various environmental conditions prior to its actual deployment. The Chli-DeWilde agent stability measure views a MAS as a discrete time Markov chain with a potentially unknown transition probabilities. A MAS is considered to be ...

There is a growing demand for Multi-Agent Systems (MAS) in the software industry. The autonomous agent interaction in a dynamic software environment can potentially lead to runtime behavioral failures including deadlock. In order to bring MAS to the main stream of commercial software development, the behavior of MAS must be tested and monitored against the risk of unwanted emergent behaviors in...

This paper introduces the notion of artifact as a first-class abstraction in MASs (multi-agent systems) and focuses on its impact onion in MASs (multi-agent systems) and focuses on its impact on MAS programming. Artifacts are runtime devices providing some kind of function or service which agents can fruitfully use – both individually and collectively – to achieve their individual as well as so...

The seamless retrieval of information distributed across networks has been one of the key goals of many systems. Early solutions involved the use of single static agents which would retrieve the unfiltered data and then process it. However, this was deemed costly and inefficient in terms of the bandwidth since complete files need to be downloaded when only a single value is often all that is re...

Testing and Debugging multi-agent systems (MAS) which are inherently concurrent and distributed – is a challenging task. While complex application scenarios demand intelligent entities with autonomous reasoning capabilities, the applied reasoning mechanisms impair current approaches to validate MAS implementations. Reactive planning systems, namely the well-known Belief Desire Intention (BDI) a...

Cloud computing can offer a very powerful, reliable, predictable and scalable computing infrastructure for the execution of MAS (multi-agent systems) implementing complex agent-based applications such when modelling, simulation and real-time running of complex systems must be provided. Multi-agent systems appears as an adequate approach to current challenges in many areas. Between important qua...