[PDF][PDF] Lifelong machine learning systems: Beyond learning algorithms
Abstract Lifelong Machine Learning, or LML, considers systems that can learn many tasks
from one or more domains over its lifetime. The goal is to sequentially retain learned …
from one or more domains over its lifetime. The goal is to sequentially retain learned …
[書籍][B] Real life applications of soft computing
Rapid advancements in the application of soft computing tools and techniques have proven
valuable in the development of highly scalable systems. Although many resources on the …
valuable in the development of highly scalable systems. Although many resources on the …
CS Freiburg: coordinating robots for successful soccer playing
T Weigel, JS Gutmann, M Dietl… - IEEE Transactions on …, 2002 - ieeexplore.ieee.org
Robotic soccer is a challenging research domain because many different research areas
have to be addressed in order to create a successful team of robot players. The paper …
have to be addressed in order to create a successful team of robot players. The paper …
A case-based approach for coordinated action selection in robot soccer
Designing coordinated robot behaviors in uncertain, dynamic, real-time, adversarial
environments, such as in robot soccer, is very challenging. In this work we present a case …
environments, such as in robot soccer, is very challenging. In this work we present a case …
Machine learning with AIBO robots in the four-legged league of RoboCup
SK Chalup, CL Murch… - IEEE Transactions on …, 2007 - ieeexplore.ieee.org
Robot learning is a growing area of research at the intersection of robotics and machine
learning. The main contributions of this paper include a review of how machine learning has …
learning. The main contributions of this paper include a review of how machine learning has …
Robot adaptation to unstructured terrains by joint representation and apprenticeship learning
When a mobile robot is deployed in a field environment, eg, during a disaster response
application, the capability of adapting its navigational behaviors to unstructured terrains is …
application, the capability of adapting its navigational behaviors to unstructured terrains is …
Robot perceptual adaptation to environment changes for long-term human teammate following
Perception is one of the several fundamental abilities required by robots, and it also poses
significant challenges, especially in real-world field applications. Long-term autonomy …
significant challenges, especially in real-world field applications. Long-term autonomy …
Enhancing consistent ground maneuverability by robot adaptation to complex off-road terrains
Terrain adaptation is a critical ability for a ground robot to effectively traverse unstructured off-
road terrain in real-world field environments such as forests. However, the expected or …
road terrain in real-world field environments such as forests. However, the expected or …
Reinforcement learning on an omnidirectional mobile robot
R Hafner, M Riedmiller - … Robots and Systems (IROS 2003)(Cat …, 2003 - ieeexplore.ieee.org
With this paper we describe a well suited, scalable problem for reinforcement learning
approaches in the field of mobile robots. We show a suitable representation of the problem …
approaches in the field of mobile robots. We show a suitable representation of the problem …
Fusion of multiple behaviors using layered reinforcement learning
This study introduces a method to enable a robot to learn how to perform new tasks through
human demonstration and independent practice. The proposed process consists of two …
human demonstration and independent practice. The proposed process consists of two …