Interactive embodied evolution for socially adept Artificial General Creatures (2407.21357v1)
Abstract: We introduce here the concept of Artificial General Creatures (AGC) which encompasses "robotic or virtual agents with a wide enough range of capabilities to ensure their continued survival". With this in mind, we propose a research line aimed at incrementally building both the technology and the trustworthiness of AGC. The core element in this approach is that trust can only be built over time, through demonstrably mutually beneficial interactions. To this end, we advocate starting from unobtrusive, nonthreatening artificial agents that would explicitly collaborate with humans, similarly to what domestic animals do. By combining multiple research fields, from Evolutionary Robotics to Neuroscience, from Ethics to Human-Machine Interaction, we aim at creating embodied, self-sustaining Artificial General Creatures that would form social and emotional connections with humans. Although they would not be able to play competitive online games or generate poems, we argue that creatures akin to artificial pets would be invaluable stepping stones toward symbiotic Artificial General Intelligence.
- A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence. Computer, 53(8):18–28.
- Practical hardware for evolvable robots. Frontiers in Robotics and AI, 10.
- Borji, A. (2023). A Categorical Archive of ChatGPT Failures. Technical report.
- Sparks of Artificial General Intelligence: Early experiments with GPT-4. Technical report.
- Clocksin, W. F. (2003). Artificial intelligence and the future. Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 361(1809):1721–1748.
- The Triangle of Life: Evolving Robots in Real-time and Real-space. In Advances in Artificial Life, ECAL 2013, pages 1056–1063. MIT Press.
- Fjelland, R. (2020). Why general artificial intelligence will not be realized. Humanities and Social Sciences Communications, 7(1):10.
- Explaining the Neuroevolution of Fighting Creatures Through Virtual fMRI. Artificial Life, 29(1):66–93.
- Goertzel, B. (2014). Artificial General Intelligence: Concept, State of the Art, and Future Prospects. Journal of Artificial General Intelligence, 5(1):1–48.
- Kateman, B. (2024). AI Should Be Terrified of Humans. Time.
- Kriegman, S. (2019). Why virtual creatures matter. Nature Machine Intelligence, 1(10):492–492.
- The Effects of Learning in Morphologically Evolving Robot Systems. Frontiers in Robotics and AI, 9:797393.
- Evolving-Controllers Versus Learning-Controllers for Morphologically Evolvable Robots. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 12104 LNCS, pages 86–99. Springer.
- Playing Atari with Deep Reinforcement Learning.
- Moral consideration of nonhumans in the ethics of artificial intelligence. AI and Ethics, 1(4):517–528.
- Contemporary Approaches to Artificial General Intelligence. In Artificial General Intelligence, pages 1–30. Springer Berlin Heidelberg, Berlin, Heidelberg.
- How the Body Shapes the Way We Think. In How the Body Shapes the Way We Think, page 394. MIT Press.
- Interdependence as the key for an ethical artificial autonomy. AI & SOCIETY.
- BEYOND MAD?: The Race For Artificial General Intelligence. ITU Journal: ICT Discoveries, Special Issue, 1(1):8.
- How Organisms Come to Know the World: Fundamental Limits on Artificial General Intelligence. Frontiers in Ecology and Evolution, 9:806283.
- Moral consideration for AI systems by 2030. AI and Ethics, 1:1–16.
- Heuristic problem solving: The next advance in operations research. Operations Research.
- Responses to catastrophic AGI risk: A survey. Physica Scripta, 90(1):018001.
- Designing neural networks through neuroevolution. Nature Machine Intelligence, 1(1):24–35.
- Ci-group/revolve2: 1.2.0. Zenodo.