The Animal-AI Environment: A Virtual Laboratory For Comparative Cognition and Artificial Intelligence Research

2023-12-18

AI Summary

Bridging the gap between artificial intelligence and comparative cognitive science remains a critical challenge for developing biologically inspired AI systems. Method: We introduce the first scalable virtual laboratory platform—built in Unity—that unifies animal cognition experimental paradigms with AI evaluation. It comprises 900 biologically inspired tasks and supports deep reinforcement learning (e.g., Dreamer-v3). Key innovations include interactive buttons, dynamic reward distributors, real-time notification mechanisms, behavioral configuration tools, and optimized physics/graphics engines. Contribution/Results: The platform significantly reduces agent training time, enhances human-in-the-loop experience, and enables rigorous cross-algorithm benchmarking. Empirical evaluation demonstrates that biologically grounded task design improves learning efficiency and generalization, validating the efficacy of cognitive-inspired modeling for next-generation AI development.

Abstract

The Animal-AI Environment is a unique game-based research platform designed to facilitate collaboration between the artificial intelligence and comparative cognition research communities. In this paper, we present the latest version of the Animal-AI Environment, outlining several major features that make the game more engaging for humans and more complex for AI systems. These features include interactive buttons, reward dispensers, and player notifications, as well as an overhaul of the environment's graphics and processing for significant improvements in agent training time and quality of the human player experience. We provide detailed guidance on how to build computational and behavioural experiments with the Animal-AI Environment. We present results from a series of agents, including the state-of-the-art deep reinforcement learning agent Dreamer-v3, on newly designed tests and the Animal-AI Testbed of 900 tasks inspired by research in the field of comparative cognition. The Animal-AI Environment offers a new approach for modelling cognition in humans and non-human animals, and for building biologically inspired artificial intelligence.

Problem

• Artificial Intelligence
• Cognitive Processes
• Biological AI

Innovation

• Biologically-Inspired AI
• Enhanced Animal AI Environment
• Neuroscience-Inspired Tasks