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Goal Sequence Achievement Using Higher-Order Neural Connectionsin Construction

This paper describes a neural architecture for selecting and achieving sequences of goals. The architecture is tested on a wall-construction task in a two dimensional environment containing circular objects. Scavenger agents bring building materials to a site while builder agents use the material to construct a wall. The agents are robust, that is, they stop to eat and drink when hungry or thirsty and they are able to recover from failed conditions and incomplete steps.