A hybrid approach to learn, retrieve and reuse qualitative cases
Thiago Pedro Donadon Homem, Danilo H. Perico, Paulo Eduardo Santos, Anna Helena Reali Costa, Reinaldo A. C. Bianchi, Ramón López de Mántaras · 2017
The application of Artificial Intelligence methods is becoming indispensable in several domains, for instance in credit card fraud detection, voice recognition, autonomous cars and robotics. However, some methods fail in performances or solving some problems, and hybrid approaches can outperform the results when compared to traditional ones. In this paper we present a hybrid approach, named qualitative case-based reasoning and learning (QCBRL), that integrates three well-known AI methods: Qualitative Spatial Reasoning, Case-Based Reasoning and Reinforcement Learning. QCBRL system was designed to allow an agent to learn, retrieve and reuse qualitative cases in the robot soccer domain. We applied our method in the Half-Field Offense and we have obtained promising results.