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Modern business goals are often fulfilled with workflows that may cross many organisations and utilise services on a variety of devices and/or supported by different platforms. Current workflows are inherently context-aware. Each context is governed and constrained by its own policies and rules to prevent unauthorised participants from executing sensitive tasks and also to prevent tasks from accessing...
The web is one of the most important mean of disseminating maps to users worldwide. These maps are commonly generated, on-the-fly, by extracting and displaying pre-processed data which is stored beforehand in specific databases. Though rapid, this approach lacks flexibility and does not necessarily provide the user with all the relevant spatial data at the right time and in the right way. Indeed,...
We present a mediation system, developed to give support to participants in mechanical-system-designer activities. Sufficient assistance is needed to facilitate and coordinate actors' activities. To accomplish this goal we introduce an artificial actor: Mediator. Mediator takes part to collaborative activity, with a specific role of facilitating cooperation between designers. This role of assistance,...
The Multi-agents computing paradigm offers support for large scale, widely distributed, high-performance computational systems. Several of such architectures and frameworks have been developed aimed at primarily computations in support of scientific, engineering calculations and managements. On the other hand agent software provides a number of issues including; autonomous, integrity, flexibility,...
Sufficient test coverage for Software Agents that operate in an open and dynamic environment is unlikely to be achieved during the agents' development. Especially when agents exhibit self properties and are constantly adapting to changes in their environment it is important to limit their autonomy to ensure that their behaviour lies within safe boundaries. To increase the trust in the agents, once...
Research in learning and planning in real-time strategy (RTS) games is very interesting in several industries such as military industry, robotics, and most importantly game industry. A recent published work on online case-based planning in RTS Games does not include the capability of online learning from experience, so the knowledge certainty remains constant, which leads to inefficient decisions...
In this paper we analyze the consensus in groups of decision makers that rank alternatives by means of weak orders. We have introduced the class of weighted Kemeny distances on weak orders for taking into account where the disagreements occur, and we have analyzed the properties of the associated consensus measures.
This paper proposes a novel multiagent system for complex system modeling based on a dynamic fuzzy cognitive map approach. It aims to represent the domain knowledge and carry out the inference process regarding the uncertainty, distribution and dynamism that exist in most of real world problems. The proposed multiagent system architecture is able to model dynamic real world problems that almost contain...
Agent reasoning in large scale multi-agent systems requires techniques which often work with uncertainty and probability. In our research, we use trust and reputation principles to support agent reasoning and decisioning. Information about agents past behaviour and their qualities are transformed to multi-context trust. It allows to view a single agent from different point of views, because agents...
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