Machine Learning: Principles and Techniques (Chapman and Hall Computing Series)

Part 1: Background The logic of induction - Richard Forsyth Machine induction as a form of knowledge acquisition in knowledge engineering - Anna Hart Inductive learning: the user's perspective - Tomasz Arciszewski and M. Mustafa Part 2: Biologically inspired systems The evolution of intelligence - Richard Forsyth Artificial evolution and artificial intelligence - Ingo Rechenberg Learning and distributed memory: getting close to neurons - Igor Aleksander Part 3: Automated discovery Automated discovery - Kenneth Haase The acquisition of natural language by machine - Chris Naylor A computational model of creativity - Masoud Yazdani Part 4: Long-term perspectives The road to knowledge-rich learning - Roy Rada Databases that learn - Derek Partridge Cognitive architecture and connectionism - Ajit Narayanan Machine learning: the next ten years - Dimitris Chorafas.