Angielski
Robot Learning is intended for one term advanced Machine Learning courses taken by students from different computer science research disciplines. This text has all the features of a renowned best selling text. It gives a focused introduction to the primary themes in a Robot learning course and demonstrates the relevance and practicality of various Machine Learning algorithms to a wide variety of real-world applications from evolutionary techniques to reinforcement learning, classification, control, uncertainty and many other important fields.
Salient features:
- Comprehensive coverage of Evolutionary Techniques, Reinforcement Learning and Uncertainty.
- Precise mathematical language used without excessive formalism and abstraction.
- Included applications demonstrate the utility of the subject in terms of real-world problems.
- A separate chapter on Anticipatory-mechanisms-of-human-sensory-motor-coordination and biped locomotion.
- Collection of most recent research on Robot Learning.
