Multi-Agent Participatory Simulations Between Experimental Economics and Role-Playing Games

Reviewing Agent-Based Modelling of Socio-Ecosystems: A Methodology for the Analysis of Climate Change Adaptation and Sustainability

“…In the spirit of adaptive management (Holling 1978) several researchers 2 have developed their agent-based models together with the stakeholders of the problem under concern, improving the acquisition of knowledge, the model construction, the model validation and the model application to decision making (e.g. Bousquet et al 1999;Barreteau et al 2001;Guyot and Honiden 2006).…”

“…The main advantages of ABM are found in its abilities to: (a) couple social and environmental systems, linking social and environmental processes; (b) model individual decision-making entities, taking into account the interactions between them and incorporating social processes and nonmonetary influences; (c) incorporate the influence of micro-level decision making into the system dynamics, linking these micro-scale decisions to macro-scale phenomena; (d) study the emergence of collective responses to changing environment and policies (Hare and Deadman 2004;Matthews et al 2007). Moreover, agent-based models can be constructed and validated in the participatory setting, fostering the process of social learning and, while integrating factual and local knowledge, they can provide assistance for specific decision making (Barreteau, Bousquet, and Attonaty 2001;Guyot and Honiden 2006;Pahl-Wostl 2007).…”

A Serious Game for Exploring and Training in Participatory Management of National Parks for Biodiversity Conservation: Design and Experience

“…Participatory simulation and its standard bearer, the Simulación framework [Guyot and Honiden 2006], focused on a distributed support for role-playing and negotiation between human players. All interactions are recorded for further analysis (thus opening the way to automated acquisition of behavioral models) and assistant agents are provided to assist and suggest strategies to the players.…”

“…In a next stage, we plan to use automated analysis of recorded traces of interaction between human players in order to infer models of artificial players. In some previous work [Guyot and Honiden 2006], genetic programming had been used as a technique to infer interaction models, but we also plan to explore alternative induction and machine learning techniques, e.g., inductive logic programming.…”

Realistic Modeling of Agents in Crowd Simulations

“…These type of models failed to simulate the situations when high density crowd is encountered as agents get limited only to restricted moments, therefore during turbulent flow situation, it fails to portray well these situations. Later, [3] the game based models have introduced the plenty based payoff rules to improve the collision avoidance rules. But still it lacks in mimicking the turbulent flows in high density crowds efficiently.…”