Abstract
We present ACACIA, an agent-based program implemented in Java StarLogo 2.0 that simulates a two-dimensional microworld populated by agents, obstacles and goals. Our program simulates how agents can reach long-term goals by following sensorial-motor couplings (SMCs) that control how the agents interact with their environment and other agents through a process of local categorization. Thus, while acting in accordance with this set of SMCs, the agents reach their goals through the emergence of global behaviors. This agent-based simulation program would allow us to understand some psychological processes such as planning behavior from the point of view that the complexity of these processes is the result of agent–environment interaction.
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Acknowledgments
This research project was supported by grants from the Directorate General for Research of the Government of Catalonia (2001SGR-00140), the Directorate General for Higher Education and Culture of the Spanish Government (BSO 2001-2844) and the French Institut National de Recherche en Informatique et en Automatique (02N81/0011). This research project was also supported by funds from the European Union’s FEDER program. The authors would like to thank two anonymous reviewers for their comments on an earlier version of the manuscript.
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Beltran, F.S., Quera, V., Zibetti, E. et al. ACACIA: an agent-based program for simulating behavior to reach long-term goals. Cogn Process 10, 95–99 (2009). https://doi.org/10.1007/s10339-008-0236-9
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DOI: https://doi.org/10.1007/s10339-008-0236-9