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Recent advances in artificial intelligence have been strongly driven by theuse of game environments for training and evaluating agents. Games are oftenaccessible and versatile, with well-defined state-transitions and goalsallowing for intensive training and experimentation. However, agents trained ina particular environment are usually tested on the same or slightly varieddistributions, and solutions do not necessarily imply any understanding. If wewant AI systems that can model and understand their environment, we needenvironments that explicitly test for this. Inspired by the extensiveliterature on animal cognition, we present an environment that keeps all thepositive elements of standard gaming environments, but is explicitly designedfor the testing of animal-like artificial cognition.

The Animal-AI Environment: Training and Testing Animal-Like Artificial Cognition