A fundamental difficulty faced by cooperative multiagent systems is to find how to efficiently coordinate agents. There are three fundamental processes to solve the coordination problem: mutual adjustment, direct supervision and standardization. In this paper, we present our results, obtained in the RoboCupRescue environment, comparing those coordination approaches to find which one is the best...

In this paper we present X-Learn, an XML-based, multiagent system for supporting “user-device” adaptive e-learning. X-Learn is characterized by the following features: (i) it is highly subjective, since it handles quite a rich and detailed user profile that plays a key role during the learning activities; (ii) it is dynamic and flexible, i.e., it is capable of reacting to variations of exigenci...

This paper presents an architecture of an agent-based decision support system (ADSS) for ecological-medical situation assessment. The system receives statistical information in form of direct and indirect pollution indicator values. The ultimate goal of the modeled multi-agent system (MAS) is to evaluate the impact of the exposure to pollutants in population health. The proposed ADSS interacts ...

The goal is the development of a simultaneous, dynamic, technological as well as logistical real-time planning and an organizational control of the production by the production units themselves, working in the production network under the use of Multi-Agent-Technology. The design of the multi-agent-based manufacturing management system, the models of the single agents, algorithms for the agent-...

STIT is a logic of agency that has been proposed in the nineties in the domain of philosophy of action. It is the logic of constructions of the form “agent a sees to it that φ”. We believe that STIT theory may contribute to the logical analysis of multiagent systems. To support this claim, in this paper we show that there is a close relationship with more recent logics for multiagent systems. W...

We present the Transportation And Production Agent-based Simulator (TAPAS), which is an agent-based model for simulation of transport chains that can be used, e.g., for analysis of transport-related policy and infrastructure measures. TAPAS is more powerful than traditional approaches to freight transport analysis, as it explicitly models production and customer demand, and it captures the inte...

200 words) Our research focuses on understanding and analyzing prediction markets using multi-agent system and game theory-based tools. Our research attempts to address some of the shortcomings in the state-of-the-art techniques used in prediction markets. First, we develop a multi-agent system that relaxes some of the limiting assumptions made by the existing models on the behavior of the mark...

We present a framework to model the dynamics of Multiagent Q-learning with -greedy exploration. The applicability of the framework is tested through experiments in typical games selected from the literature.