How does someone react when he faces a critical situation in his life? In this paper we present an initial initial implementation architecture based on a simulation model described in [10] In our model we mainly consider the interactions between a person concerned and factors like his environment and his own abilities. Using the empolis information access suite, we currently implement our model...

Integration of advice is intended to acquire knowledge from an agent with more comprehensive information. This paper describes Arian, a general architecture for advice integration. Advice is injected into the system using the advice model which is a case in a CBR system. The architecture comprises an advice adapter to model incomming advice as cases of a CBR system. The Arian architecture is a ...

Abs t rac t . This paper presents our approach for knowledge acquisition from multiple experts. In order to build a cooperative KBS, representing the knowledge of several experts and intended to multiple users inside an organization, we propose a model of cognitive agent for guiding the process of knowledge acquisition. This model of agent can serve as a basis for specifying the future KBS to b...

Driven by the urging need to thoroughly identify and accentuate the merits of agent technology, we present in this paper MEANDER, an integrated framework for evaluating the performance of agent-based systems. The proposed framework is based on the Agent Performance Evaluation (APE) methodology, which provides guidelines and representation tools for performance metrics, measurement collection an...

This paper proposes a new method to model supply chains. Distributed systems need continuous and up-to-date information about their products, rooting process and consumption, in order to cover customer’s needs and to solve problems emerging during the products rooting. The main goal is the satisfaction of every entity constituting the logistics organization. To achieve this goal, we propose a m...

This work introduces a new evolutionary approach to solving the problems of multiobjective optimization. Novelty of the proposed method consists in the application of an evolutionary multi-agent system equipped with the mechanism(s) of elitism, instead of its ’classical’ (non-elitist) version. In the paper the model of an elitist evolutionary multi-agent system is described together with its sa...

This paper focuses on the features of belief change in a multiagent context. Agents have to consider information received from the other agents and the ability of how to change beliefs after receiving a message is a prerequisite for many multi-agents problems. The agents are embedded in an environment where they are communicating and they have to prevent potential internal conflicts in their be...

Inspired by multifunctional neural networks in biological brain, this paper is concerned with building multifunctional learning ability for artiicial neural networks. A multiagent based evolutionary artiicial neural network with lifetime learning (MENL) is used to learn two kinds of navigation abilities together: to explore unknown environments as far as possible and to reach designated goals i...

In this paper we model knowledge dynamics in agents’ belief bases in a collaborative multiagent system. Four change operators are introduced: expansion, contraction, prioritized revision, and non-prioritized revision. For all of them, both constructive definitions and an axiomatic characterization by representation theorems are given. We formally justify minimal change, consistency maintenance,...