TY  - CHAP
AU  - Dennis Barrios-Aranibar
AU  - Luiz M. G. Gonçalves
ED  - Meng Joo Er 
ED  - Yi Zhou
Y1  - 2009-01-01
PY  - 2009
T1  - Influence Value Q-Learning: A Reinforcement Learning Algorithm for Multi Agent Systems
N2  - Even since computers were invented, many researchers have been trying to understand how human beings learn and many interesting paradigms and approaches towards emulating human learning abilities have been proposed. The ability of learning is one of the central features of human intelligence, which makes it an important ingredient in both traditional Artificial Intelligence (AI) and emerging Cognitive Science. Machine Learning (ML) draws upon ideas from a diverse set of disciplines, including AI, Probability and Statistics, Computational Complexity, Information Theory, Psychology and Neurobiology, Control Theory and Philosophy. ML involves broad topics including Fuzzy Logic, Neural Networks (NNs), Evolutionary Algorithms (EAs), Probability and Statistics, Decision Trees, etc. Real-world applications of ML are widespread such as Pattern Recognition, Data Mining, Gaming, Bio-science, Telecommunications, Control and Robotics applications. This books reports the latest developments and futuristic trends in ML.
BT  - Theory and Novel Applications of Machine Learning
SP  - Ch. 6
UR  - https://doi.org/10.5772/6675
DO  - 10.5772/6675
SN  - 
PB  - IntechOpen
CY  - Rijeka
Y2  - 2024-04-18
ER  -