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