Economic Theory of Renewable Resource Management: A Multi-agent System Approach Export

@incollection{Antona, abstract = {Multi-agent methodology is used for various purposes, such as distributed solving problem, network management, etc. Multi-agent systems are also used for simulation. Usually, the emergence of macroscopic properties is studied by simulating the behavior of agents and their interactions at a microscopic level. It is a bottom-up approach. Recently emphasis has been placed on the links between the macroscopic and the microscopic levels combining the bottom-up and top down directions. We are currently developing a multi-agent simulator to illustrate and discuss the principles of the economic theory of renewable resource management. The management of renewable resources, from an economic point of view, may be based on public interventions at the macroscopic level or on regulation at the microscopic level. The simulator uses the Cormas environment [Bousquet et al., submitted]. First, a renewable resource dynamics is simulated on a theoretical grid. Second, economic agents are represented. Different agents, belonging to different stages of an industry, are represented. Agents collect the resources and others use this resource as an input for transformation. The agents' behavior and objectives are heterogeneous. Economic exchanges are simulated. We reproduce the market-oriented approach [Cheng \& Wellman, 1996] which assumes that a general equilibrium sets a global price. We also simulate the trade rules proposed by Epstein and Axtell (1996) in which there is no global price. The aim is to evaluate the differences between these two approaches from the ecological and economic points of view. Third, when an industry is established we simulate various actions at the macroscopic level. Economic theory proposes various interventions such as taxes, quotas, trade and market organization. We test these actions and observe their effects on the society of agents. We observe the quantity of resources, the benefits to the agents, the rent obtained from the macroscopic interventions and how it is shared. This simulator provides a didactic framework to explain economic theory for resource management. Later, we will use it for field study by importing field data. From the computer science point of view, this simulator will be used to test various algorithms for agent coordination. From an economic point of view, it introduces the notion of space and a time frame in the scope of resource management.}, author = {Antona, M. and Bousquet, F. and Lepage, C. and Weber, J. and Karsenty, A. and Guizol, P.}, booktitle = {Multi-Agent Systems and Agent-Based Simulation, MABS'98}, citeulike-article-id = {2316369}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/10692956_5}, comment = {A bit tricky to find that one in electronic copy at UofA. Go to "Lecture Notes in Computer Science" and then from SpringerLink page select 1556-1532. This paper is in volume 1534.}, doi = {10.1007/10692956_5}, editor = {Sichman, Jaime S. and Conte, Rosaria and Gilbert, Nigel}, journal = {Lecture Notes in Artificial Intelligence}, keywords = {agent-based, multi-agent, simulation}, pages = {61--78}, posted-at = {2008-01-31 20:57:27}, priority = {5}, series = {Lecture Notes in Computer Science}, title = {Economic Theory of Renewable Resource Management: A Multi-agent System Approach}, url = {http://dx.doi.org/10.1007/10692956_5}, volume = {1534}, year = {1998} }

TY - CHAP ID - Antona L3 - citeulike-article-id:2316369 N2 - Multi-agent methodology is used for various purposes, such as distributed solving problem, network management, etc. Multi-agent systems are also used for simulation. Usually, the emergence of macroscopic properties is studied by simulating the behavior of agents and their interactions at a microscopic level. It is a bottom-up approach. Recently emphasis has been placed on the links between the macroscopic and the microscopic levels combining the bottom-up and top down directions. We are currently developing a multi-agent simulator to illustrate and discuss the principles of the economic theory of renewable resource management. The management of renewable resources, from an economic point of view, may be based on public interventions at the macroscopic level or on regulation at the microscopic level. The simulator uses the Cormas environment [Bousquet et al., submitted]. First, a renewable resource dynamics is simulated on a theoretical grid. Second, economic agents are represented. Different agents, belonging to different stages of an industry, are represented. Agents collect the resources and others use this resource as an input for transformation. The agents’ behavior and objectives are heterogeneous. Economic exchanges are simulated. We reproduce the market-oriented approach [Cheng & Wellman, 1996] which assumes that a general equilibrium sets a global price. We also simulate the trade rules proposed by Epstein and Axtell (1996) in which there is no global price. The aim is to evaluate the differences between these two approaches from the ecological and economic points of view. Third, when an industry is established we simulate various actions at the macroscopic level. Economic theory proposes various interventions such as taxes, quotas, trade and market organization. We test these actions and observe their effects on the society of agents. We observe the quantity of resources, the benefits to the agents, the rent obtained from the macroscopic interventions and how it is shared. This simulator provides a didactic framework to explain economic theory for resource management. Later, we will use it for field study by importing field data. From the computer science point of view, this simulator will be used to test various algorithms for agent coordination. From an economic point of view, it introduces the notion of space and a time frame in the scope of resource management. JF - Lecture Notes in Artificial Intelligence SE - Lecture Notes in Computer Science EP - 78 TI - Economic Theory of Renewable Resource Management: A Multi-agent System Approach VL - 1534 T2 - Multi-Agent Systems and Agent-Based Simulation, MABS'98 SP - 61 KW - agent-based KW - multi-agent KW - simulation N1 - A bit tricky to find that one in electronic copy at UofA. Go to "Lecture Notes in Computer Science" and then from SpringerLink page select 1556-1532. This paper is in volume 1534. AU - Antona, M AU - Bousquet, F AU - Lepage, C AU - Weber, J AU - Karsenty, A AU - Guizol, P A2 - Sichman, Jaime A2 - Conte, Rosaria A2 - Gilbert, Nigel PY - 1998/// UR - http://dx.doi.org/10.1007/10692956_5 ER -