#IJCAI2025 distinguished paper: Combining MORL with restraining bolts to learn normative behaviour

Image provided by the authors – generated using Gemini. For many of us, artificial intelligence (AI) has become part of everyday life, and the rate at which we assign previously human roles to AI systems shows no signs of slowing down. AI systems are the crucial ingredients of many technologies -- e.g., self-driving cars, smart urban planning, digital assistants -- across a growing number of domains. At the core of many of these technologies are autonomous agents -- systems designed to act on behalf of humans and make decisions without direct supervision. In order to act effectively in the real world, these agents must be capable of carrying out a wide range of tasks despite possibly unpredictable environmental conditions, which often requires some form of machine learning (ML) for achieving adaptive behaviour.