Complex information systems require more and more advanced knowledge representation, management, and discovery tools and techniques, which converge in a collection of intelligent knowledge-based models and methodologies of emerging interest to research communities. This poses new challenges on the issue of devising innovative methodologies and paradigms in the context of a broad framework encom...

The perspective of modelling agents rather than using them for a specificed purpose entails a difference in approach. In particular an emphasis on veracity as opposed to efficiency. An approach using evolving populations of mental models is described that goes some way to meet these concerns. It is then argued that social intelligence is not merely intelligence plus interaction but should allow...

Traditional control algorithms in Automatic Train Operation (ATO) system have some drawbacks, such as high energy consumption and low riding comfort. Combined with data mining methods and driving experience, two Intelligent Train Operation (ITO) models for the subway train control are proposed. Firstly the training data set was sorted out and sieved out from the real train operation data set by...

The paper shows the state of the art of the development of systems capable to reason about the traffic behavior and evolution in similar terms to an expert traffic operator. This type of systems may not be conceived to replace the human operator but to act as intelligent assistants that cooperate in the task of defining and applying traffic control decisions. Such concept of system is that of t...

The importance of research for rapid and automated model construction of decision support systems is prominent and recognized. In the literature, research on model construction methods has been conducted using either component-based approaches or artificial intelligent approaches; however, these methods are usually incapable of handling dynamic constrains under different situations. To obtain s...

An underlying problem of current interface agent research is the failure to adequately address e ective and e cient knowledge representations and associated methodologies suitable for modeling the users' interactions with the system. These user models lack the representational complexity to manage the uncertainty and dynamics involved in predicting user intent and modeling user behavior. A util...

An on-line approach for rule-base evolution by recursive adaptation of rule structure and parameters in is described in the paper. An integral part of the procedure is to maximise the model transparency by simplifying the fuzzy linguistic descriptions of the input variables. The rule base evolves over time and utilising direct calculation approaches and hence minimising the reliance on the use ...

Recent studies in multi-agent systems are paying increasingly more attention to the paradigm of designing intelligent agents with human inspired concepts. One of the main cognitive concepts driving the core of many recent approaches in multi agent systems is shared mental models. In this paper, we propose an architecture for sharing mental models based on a new concept called semantic movement....