The increasing complexity and unpredictability of many ICT scenarios let us envision that future systems will have to dynamically learn how to act and adapt to face evolving situations with little or no a priori knowledge, both at the level of individual components and at the collective level. In other words, such systems should become able to autonomously develop models of themselves and of their environment. Autonomous development includes: learning models of own capabilities; learning how to act purposefully towards the achievement of specific goals; and learning how to act collectively, i.e., accounting for the presence of others. In this paper, we introduce the vision of autonomous development in ICT systems, by framing its key concepts and by illustrating suitable application domains. Then, we overview the many research areas that are contributing or can potentially contribute to the realization of the vision, and identify some key research challenges.

Instead, Ford will be putting its driverless cars on Lyft's open autonomous platform, which gives auto companies access to Lyft's logistical software and data from its network of rides. Ford's autonomous test cars will also be added to the Lyft network, and will eventually be used to pick up passengers when the tech is deemed reliable enough for public use. The automaker has established itself as a major player in self-driving development, investing $1 billion in start-up Argo AI and promoting the head of its autonomous development wing to CEO. Uber is dealing with a major lawsuit brought by Waymo parent company Alphabet, which has put the ride-hailing company's self-driving program under scrutiny.