In this paper we introduce and discuss the apprentice framework, which we speculate can be used to plan and evaluate computational creativity projects. The framework defines a sequence of phases a system must follow in order to reach a level of creativity acceptable to a set of human judges. It also establishes four aspects of a creative piece susceptible of creative work. We mention some examp...

In this paper, we devise inverse reinforcement learning (RL) algorithms for nonlinear continuous-time systems described by multiplayer differential equations. We define a new class of Multi-player Noncooperative Apprentice Games, in which both the expert and learner have N-player control inputs. The games are solved learners reconstructing unknown performance reward functions experts from exper...

We give a general overview of C U N T , a userfriendly interactive concept-learner, which can be used as a module for Learning Apprentice Systems. CLINT combines several interesting features : it uses domain-knowledge, generates examples, copes with indirect relevance, shifts its bias, recovers from errors and identifies concepts in the limit.