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We present an approach to multi-agent navigation, that is based on generating potential-fields from A*-paths. We will introduce and compare two algorithms: 1) a geometrical algorithm that is based on quads, and 2) an images-based algorithm. We show empirically that the images-based algorithm is more memory-consuming, but has better performance.
Over the past decade Multi-Agent Systems (MAS) have emerged as a successful approach to develop distributed applications. In recent years proposals have been made to extend MAS models with probabilistic behavior. Languages to reason about such systems were presented in order to deal with uncertainty that can be encountered in practical application domains. While in recent works model checking techniques...
It has been observed that there are interesting relations between planning and agent programming. This is not surprising as agent programming was partially motivated by the lack of planners that are able to operate in dynamic, complex environments. Vice versa it has also been observed, however, that agent programming languages typically lack planning capabilities. We show in this paper that the agent...
The formalization and use of experiences in good model design would make an important contribution to increasing the efficiency of modeling as well as to supporting the knowledge transfer from experienced modelers to modeling novices. We propose to address this problem by providing a set of model design patterns inspired by patterns in Software Engineering for capturing the reusable essence of a solution...
There is an increasing interest on ensemble learning since it reduces the bias-variance problem of several classifiers. In this paper we approach an ensemble learning method in a multi-agent environment. Particularly, we use genetic algorithms to learnt weights in a boosting scenario where several case-based reasoning agents cooperate. In order to deal with the genetic algorithm results, we propose...
The paper addresses the tasks of monitoring and diagnosing the execution of a Multi-Agent Plan, taking into account a very challenging scenario where the degree of system observability may be so low that an agent may not have enough information for univocally determining the outcome of the actions it executes (i.e., pending outcomes). The paper discusses how the ambiguous results of the monitoring...
Multi-agent systems where agents compete against one another in a specific environment pose challenges in relation to the trust modeling of an agent aimed at ensuring the right decisions are taken. A lot of literature has focused on describing trust models, but less in developing strategies to use them optimally. In this paper we propose a decision-making strategy that uses the information provided...
In recent years, damage caused by DoS attacks is real and causing substantive problems. Such threat is widespread from major commercial sites to individual users. Therefore, it is important for network administrators to develop means to comprehend the latest trend of DoS attacks. In this paper, we propose a distributed detecting method for SYN Flood attack which exploits a flow in TCP itself. Our...
Today’s supply chains span across continents, involve numerous entities with different dynamics, and contend with various uncertainties. This paper presents an agent-based model for decision support in a multi-site lube additive manufacturing enterprise. The supply chain comprises raw material suppliers, the lube additive enterprise, and customers. The enterprise consists of a central sales department...
Agents and Artifacts model extended with organisation promotes artifact based environments aimed at supporting multiagent coordination and goal oriented interactions and communication. Nevertheless, the use of artifacts for organisational purposes constrains agents to be aware of complex structures described in an organisational specification: an organisational specification: for instance, agents...
In this paper, we describe the multiagent supply chain simulation framework MACSIMA that allows the design of large-scale supply network topologies consisting of a multitude of autonomous agents. MACSIMA provides all agents with an adaptive negotiation module providing the fine-tuning of learning capabilities on the basis of genetic algorithms as well as of settings controlling the exchange of information...
Concerning distributed energy management, virtual power plants are a frequently discussed topic. Although there are several different approaches to the coordination of distributed energy resources in this context, the inherent dynamics of this complex task especially relating to reactive scheduling have mostly been neglected. As a consequence, this paper discusses MARS, a multiagent-based coordination...
In constraint satisfaction, decomposition is a common technique to split a problem in a number of parts in such a way that the global solution can be efficiently assembled from the solutions of the parts. In this paper, we study the decomposition problem from an autonomous agent perspective. Here, a constraint problem has to be solved by different agents each controlling a disjoint set of variables...
We introduce a ride-sharing concept for short distance travel within metropolitan areas which is designed to handle spontaneous ride-sharing requests of prospective passengers with transport opportunities available on short call. The system has been designed as a multiagent system. We present a methodology to determine the feasibility of our ride-sharing approach for specific metropolitan areas and...
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