Simulations of predator-prey equations across 220,000 parameter sets show habituation, sensitization, and discrete number learning in recovery times, with strong asymmetry between response magnitude and recovery time.
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PALMS is a computational tool implementing canonical and attentional Pavlovian learning models with support for large experiments and a new unified learning rate variant that combines Mackintosh and Pearce-Hall ideas.
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Training Ecosystems: A Computational Approach to Uncovering Learning Behavior in Unconventional Contexts
Simulations of predator-prey equations across 220,000 parameter sets show habituation, sensitization, and discrete number learning in recovery times, with strong asymmetry between response magnitude and recovery time.
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PALMS: A Computational Implementation for Pavlovian Associative Learning Models' Simulation
PALMS is a computational tool implementing canonical and attentional Pavlovian learning models with support for large experiments and a new unified learning rate variant that combines Mackintosh and Pearce-Hall ideas.