Scientific discovery: computational explorations of the creative process
Scientific discovery: computational explorations of the creative process
Learning concepts from sensor data of a mobile robot
Machine Learning - Special issue on robot learning
Learning to guide a robot via perceptions
New directions in AI planning
Prolog (3rd ed.): programming for artificial intelligence
Prolog (3rd ed.): programming for artificial intelligence
Discovery as Autonomous Learning from the Environment
Machine Learning
Predicate Invention and Learning from Positive Examples Only
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Relational Reinforcement Learning
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Learning planning rules in noisy stochastic worlds
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Learning novel domains through curiosity and conjecture
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Discovery of abstract concepts by a robot
DS'10 Proceedings of the 13th international conference on Discovery science
Autonomous discovery of abstract concepts by a robot
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part I
Learning from noisy data using a non-covering ILP algorithm
ILP'10 Proceedings of the 20th international conference on Inductive logic programming
Inductive Logic Programming ILP and Reasoning by Analogy in Context of Embodied Robot Learning
International Journal of Agent Technologies and Systems
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We describe an experiment in the application of ILP to autonomous discovery in a robotic domain. An autonomous robot is performing experiments in its world, collecting data and formulating predictive theories about this world. In particular, we are interested in the robot's "gaining insights" through predicate invention. In the first experimental scenario in a pushing blocks domain, the robot discovers the notion of objects' movability. The second scenario is about discovering the notion of obstacle. We describe experiments with a simulated robot, as well as an experiment with a real robot when robot's observations contain noise.