Although creativity is studied from philosophy to cognitive robotics, a definition has proven
elusive. We argue for emphasizing the creative process (the cognition of the creative agent) …

According to cognitive psychology and related disciplines, the development of complex
problem-solving behaviour in biological agents depends on hierarchical cognitive …

Reinforcement learning (RL) allows an agent to solve sequential decision-making problems
by interacting with an environment in a trial-and-error fashion. When these environments are …

Scaling up reinforcement learning for robot control | Proceedings of the Tenth International
Conference on International Conference on Machine Learning ACM Digital Library home ACM …

Cognitive Psychology and related disciplines have identified several critical mechanisms
that enable intelligent biological agents to learn to solve complex problems. There exists …

We present a computational framework in which to explore the generation of creative
behavior in artificial systems. In particular, we adopt an evolutionary perspective of human …

In robotics, the ultimate goal of reinforcement learning is to endow robots with the ability to
learn, improve, adapt and reproduce tasks with dynamically changing constraints based on …

The ability to combine known skills to create new ones may be crucial in the solution of
complex reinforcement learning problems that unfold over extended periods. We argue that …

Reinforcement-learning (RL) algorithms are often tweaked and tuned to specific
environments when applied, calling into question whether learning can truly be considered …

Many real-world control problems involve both discrete decision variables–such as the
choice of control modes, gear switching or digital outputs–as well as continuous decision …