Learning domain knowledge for teaching procedural skills
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
A Hybrid Architecture for Situated Learning of Reactive Sequential Decision Making
Applied Intelligence
An Integrated Approach of Learning, Planning, and Execution
Journal of Intelligent and Robotic Systems
Automated Discovery: A Fusion of Multidisciplinary Principles
AI '00 Proceedings of the 13th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
The Melting Pot of Automated Discovery: Principles for a New Science
DS '99 Proceedings of the Second International Conference on Discovery Science
Using ILP to Improve Planning in Hierarchical Reinforcement Learning
ILP '00 Proceedings of the 10th International Conference on Inductive Logic Programming
Scientific discovery and inventive engineering design: cognitive and computational similarities
Formal engineering design synthesis
Looping suffix tree-based inference of partially observable hidden state
ICML '06 Proceedings of the 23rd international conference on Machine learning
An Experiment in Robot Discovery with ILP
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Journal of Artificial Intelligence Research
Automatic stimulation of experiments and learning based on prediction failure recognition
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Searching for planning operators with context-dependent and probabilistic effects
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Incremental learning of relational action models in noisy environments
ILP'10 Proceedings of the 20th international conference on Inductive logic programming
Learning by knowledge sharing in autonomous intelligent systems
IBERAMIA-SBIA'06 Proceedings of the 2nd international joint conference, and Proceedings of the 10th Ibero-American Conference on AI 18th Brazilian conference on Advances in Artificial Intelligence
Active learning of relational action models
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Automated Discovery Of Empirical Laws
Fundamenta Informaticae
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Discovery involves collaboration among many intelligent activities. However, little is known about how and in what form such collaboration occurs. In this article, a framework is proposed for autonomous systems that learn and discover from their environment. Within this framework, many intelligent activities such as perception, action, exploration, experimentation, learning, problem solving, and new term construction can be integrated in a coherent way. The framework is presented in detail through an implemented system called LIVE, and is evaluated through the performance of LIVE on several discovery tasks. The conclusion is that autonomous learning from the environment is a feasible approach for integrating the activities involved in a discovery process.