SCIENTIA AGRICULTURAE BOHEMICA, 44, 2013 (3): 189–196 189 INTRODUCTION Currently, agriculture and related industries are closely connected with advances in the area of biology and chemistry. Unfortunately, from time to time we have to cope with biological or chemical incidents. These apparently represent a considerable threat for our society and have more serious consequences than ever before. This can be explained by more sophis- ticated biological agents and chemical compounds, increasing value of endangered assets, and also by fast development of technologies within last few decades. To categorize them, one group covers incidents caused by biological or chemical weapons, while the second is represented by unintentional incidents like the leakage of a dangerous substance from a plant or laboratory, or natural incidence of a disease within animal herds. The intentional incidents are usually easier to man- age, because their focal point can be typically quickly identifiable and localized more precisely. Therefore, the critical assets can be recognized faster and adequately protected. The appropriate response to these incidents is conducted only by trained personnel, usually per- taining to police, epidemiological or armed forces. On the other hand, in the case of unintentional accidents, which occur within agricultural mills or plants, peo- ple responsible for the management of such complex and difficult tasks are usually not trained enough for prompt and professional decisions which would protect the critical assets. Therefore, the biological and chemical incidents remain a challenging as well as important task for both researchers and practition- ers. Considering the afore-mentioned reasons, a tool for decision support and for the improvement of the decision effectiveness and consequences minimization needs to be used. The objective of the present paper is to introduce the multi-agent based simulation, because it provides us with the advantages such as problem complexity elimination, incident scenario modelling, or more effective resource planning and utilization. Moreover, the demands on non-expert decision mak- ers are decreased significantly. It ensures flexible and more precise attitude to the incident management. MATERIAL AND METHODS Apparently, the management of biological and chemical incidents represents the unstructured and complex problem. For the purposes of its resolution, MANAGEMENT OF BIOLOGICAL AND CHEMICAL INCIDENTS: SIMULATION-BASED DECISION SUPPORT * T. Otčenášková, V. Bureš, P. Čech University of Hradec Králové, Hradec Králové, Czech Republic Decision making processes during biological or chemical incidents represent a challenging and demanding issue. This task is constituted by several complex activities and important decisions. In the case of unintentional accidents in agricultural plants or within related industries, these decisions have to be made by personnel often not primarily trained for such situations. Therefore any available support tool, which can increase the probability of successful management of these incidents, should be employed. The main objective is to minimize the consequences, ensure the quality of products, and protect people and animals and other crucial assets. From the technological perspective, various approaches or principles have already been ap- plied and intended for computer-based support of biological or chemical incidents management. Nevertheless, the multi-agent technologies can be also effectively utilized. As an example, this paper presents a model applicable for the management of biological or chemical incidents created in the multi-agent NetLogo environment. The main contribution to the scientifc feld includes the characterization of specifcs related to the discussed type of decision-making process. Moreover, within the paper the description of the simulation model is provided, parameterization is explained, and areas for further research are outlined. biological incident management; chemical incident management; decision making; process; multi-agent technologies; simula- tion modelling * Supported by the Grant Agency of the Czech Republic (GACR), Project No. 402/09/0662, and the Ministry of Defence & Armed Forces of the Czech Republic, Project No. MO0FVZ0000604. doi: 10.7160/sab.2013.440310