Affordances, motivations, and the world graph theory
Adaptive Behavior - Special issue on biologically inspired models of navigation
Global localization and topological map-learning for robot navigation
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
2005 Special issue: Robust self-localisation and navigation based on hippocampal place cells
Neural Networks - Special issue: Computational theories of the functions of the hippocampus
Map-Based Spatial Navigation: A Cortical Column Model for Action Planning
Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space
Map-based navigation in mobile robots
Cognitive Systems Research
Map-based navigation in mobile robots
Cognitive Systems Research
Map-Based Spatial Navigation: A Cortical Column Model for Action Planning
Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
Minimal model of strategy switching in the plus-maze navigation task
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
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For animals as well as for humans, the hypothesis of multiple memory systems involved in different navigation strategies is supported by several biological experiments. However, due to technical limitations, it remains difficult for experimentalists to elucidate how these neural systems interact. We present how a computational model of selection between navigation strategies can be used to analyse phenomena that cannot be directly observed in biological experiments. We reproduce an experiment where the rat's behaviour is assumed to be ruled by two different navigation strategies (a cue-guided and a map-based one). Using a modelling approach, we can explain the experimental results in terms of interactions between these systems, either competing or cooperating at specific moments of the experiment. Modelling such systems can help biological investigations to explain and predict the animal behaviour.