Abstract
We describe the model and the software implementation of population of simple cognitive agents, naïve creatures experiencing fear and/or desire while learning to cross a highway. The creatures use an observational learning mechanism for adoption or rejection of a strategy to cross the highway. Presented simulation results are consistent with the fact that crossing a highway becomes more difficult with increase of cars density and it is affected by the creatures’ fears and desires. The transfer the knowledge base acquired in one environment to another one combined with creatures ability to change a crossing point improves creatures success of crossing a highway.
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Lawniczak, A.T., Di Stefano, B.N., Ernst, J.B. (2014). Software Implementation of Population of Cognitive Agents Learning to Cross a Highway. In: Wąs, J., Sirakoulis, G.C., Bandini, S. (eds) Cellular Automata. ACRI 2014. Lecture Notes in Computer Science, vol 8751. Springer, Cham. https://doi.org/10.1007/978-3-319-11520-7_73
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DOI: https://doi.org/10.1007/978-3-319-11520-7_73
Publisher Name: Springer, Cham
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