INVESTIGADORES
LARROSA Juan Manuel Ceferino
congresos y reuniones científicas
Título:
Applications of Agent-Based Models in Management and Economics
Autor/es:
LARROSA, JUAN M.C.
Lugar:
Bahía Blanca
Reunión:
Congreso; Modelos y Simulación en Economía y Administración AMSE 2006; 2006
Institución organizadora:
Association for the Advancement of Modelling and Simulation Techniques in Enterprises (AMSE)- Universidad Nacional del Sur
Resumen:
Many macro-level processes that can be observed in social systems, such as crowding, over-harvesting and stock-market dynamics, emerge from the interactions between a multitude of individual agents. Here, an agent is being considered as a system that tries to fulfill a set of goals in a complex, dynamic environment, and ‘agent’ thus may refer to e.g., bacteria, plants, insects, fish, mammals, human households, firms and nations. Agent-based modelling implies that agents are being formalized as making decisions on the basis of their own goals, the information they have about the environment and their expectations regarding the future. The goals, information and expectations an agent has are being affected by interactions with other agents. Agents are adaptive, which implies that they are capable of changing their decision strategies and consequently their behavior. Social sciences have evolved by adopting these newer methodological tools for testing their theoretical and empirical hypothesis. Specifically, Economics and Management sciences have been traditionally prone to advance in knowledge exploration through new approaches for testing hypothesis concerning allocation resources strategies and organizations. Recent literature has shown how agent-based approach can shed light to newer into former hard computable problems. We survey literature on applications of agent-based modelling in Economics and Management applications. We detect preeminence in Economics for using ABM mainly as a theoretical tool for testing economic theory propositions. On the other hand, the relatively few cases found on Management applications are focused in well grounded and realistic problems.
rds']