This paper introduces the capabilities of Agent Academy in the area of Safety Management and Hazard Control Systems. Agent Academy is a framework under development, which uses data mining techniques for training intelligent agents. This framework generates software agents with an initial degree of intelligence and trains them to manipulate complex tasks. The agents, are further integrated into a simulation multi-agent environment capable of managing issues in a hazardous environment, as well as regulating the parameters of the safety management strategy to be deployed in order to control the hazards. The initially created agents take part in long agentto-agent transactions and their activities are formed into behavioural data, which are stored in a database. As soon as the amount of collected data increases sufficiently, a data mining process is initiated, in order to extract specific trends adapted by agents and improve their intelligence. The result of the overall procedure aims to improve the simulation environment of safety management. The communication of agents as well as the architectural characteristics of the simulation environment adheres to the set of specifications imposed by the Foundation for Intelligent Physical Agents (FIPA).
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