[CARTE][B] Grundkurs künstliche intelligenz
W Ertel, NT Black - 2016 - Springer
2 1 Einführung und weichen jeder Kollision elegant aus. Wieder andere folgen anscheinend
einem Führer. Auch aggressives Verhalten kann bei einigen beobachtet werden. Sehen wir …
einem Führer. Auch aggressives Verhalten kann bei einigen beobachtet werden. Sehen wir …
Assessment of adaptive human–robot interactions
A Sekmen, P Challa - Knowledge-based systems, 2013 - Elsevier
One of the overarching goals of robotics research is that robots ultimately coexist with
people in human societies as an integral part of them. In order to achieve this goal, robots …
people in human societies as an integral part of them. In order to achieve this goal, robots …
On introducing automatic test case generation in practice: A success story and lessons learned
The level and quality of automation dramatically affects software testing activities,
determines costs and effectiveness of the testing process, and largely impacts on the quality …
determines costs and effectiveness of the testing process, and largely impacts on the quality …
AutoBlackTest: a tool for automatic black-box testing
In this paper we present AutoBlackTest, a tool for the automatic generation of test cases for
interactive applications. AutoBlackTest interacts with the application though its GUI, and …
interactive applications. AutoBlackTest interacts with the application though its GUI, and …
Q-model: An artificial intelligence based methodology for the development of autonomous robots
P Kurrek, F Zoghlami, M Jocas… - … of Computing and …, 2020 - asmedigitalcollection.asme.org
The increasing individualization of products reinforces the importance of decoupled factories
in production processes. Artificial intelligence (AI) is a recognized technology for problem …
in production processes. Artificial intelligence (AI) is a recognized technology for problem …
Open source robotic simulators platforms for teaching deep reinforcement learning algorithms
A Plasencia, Y Shichkina, I Suárez, Z Ruiz - Procedia Computer Science, 2019 - Elsevier
One of the primary goals of the artificial intelligence field is to produce fully autonomous
agents that interact with theirenvironments to learn optimal behaviors, improving over time …
agents that interact with theirenvironments to learn optimal behaviors, improving over time …
Ai motion control–a generic approach to develop control policies for robotic manipulation tasks
Current robotic solutions are able to manage specialized tasks, but they cannot perform
intelligent actions which are based on experience. Autonomous robots that are able to …
intelligent actions which are based on experience. Autonomous robots that are able to …
[PDF][PDF] Interpretable Reinforcement Learning Policies by Evolutionary Computation
D Hein - 2019 - mediatum.ub.tum.de
In this thesis, three novel algorithms for generating interpretable policies in model-based
batch reinforcement learning using particle swarm optimization and genetic programming …
batch reinforcement learning using particle swarm optimization and genetic programming …
Reinforcement learning
W Ertel - Introduction to Artificial Intelligence, 2024 - Springer
The challenging task of autonomously learning skills without the help of a teacher, solely
based on feedback from the environment to actions, is called reinforcement learning. Still …
based on feedback from the environment to actions, is called reinforcement learning. Still …
Reinforcement learning lifecycle for the design of advanced robotic systems
P Kurrek, F Zoghlami, M Jocas… - … IEEE Conference on …, 2020 - ieeexplore.ieee.org
Machine learning is a recognised technology for problem solving and accelerates the
automation by enabling systems to act independently. Cyber-physical systems based on …
automation by enabling systems to act independently. Cyber-physical systems based on …