000K  utf8
1100  $c2003
1500  eng
2050  urn:nbn:de:gbv:8:1-zs-00000168-a8
3000  Kassahun, Yohannes
3010  Sommer, Gerald
4000  Learning and Adaption$dA Comparison of Methods in Case of Navigation in an Artificial Robot World  [Kassahun, Yohannes]
4209  Neural networks, reinforcement learning systems and evolutionary algorithms are widely used to solve problems in real-world robotics. We investigate learning and adaptation capabilities of agents and show that the learning time required in continual learning is shorter than that of learning from scratch under various learning conditions. We argue that agents using appropriate hybridization of learning and evolutionary algorithms show better learning and adaptation capability as compared to agents using learning algorithms only. We support our argument with experiments, where agents learn optimal policies in an artificial robot world
4950  https://nbn-resolving.org/urn:nbn:de:gbv:8:1-zs-00000168-a8$xR$3Volltext$534
4961  https://macau.uni-kiel.de/receive/macau_mods_00001921
5051  004