Results 51 to 60 of about 2,392,451 (238)
Learning Contact-Rich Manipulation Skills with Guided Policy Search
Autonomous learning of object manipulation skills can enable robots to acquire rich behavioral repertoires that scale to the variety of objects found in the real world.
Abbeel, Pieter +2 more
core +1 more source
Applying an Ethical Lens to the Treatment of People With Multiple Sclerosis
ABSTRACT The practice of neurology requires an understanding of clinical ethics for decision‐making. In multiple sclerosis (MS) care, there are a wide range of ethical considerations that may arise. These involve shared decision‐making around selection of a disease‐modifying therapy (DMT), risks and benefits of well‐studied medications in comparison to
Methma Udawatta, Farrah J. Mateen
wiley +1 more source
ABSTRACT Purpose Air pollution has been linked to several neurological conditions, including stroke and neurodegenerative diseases. Evidence regarding its association with multiple sclerosis (MS) remains conflicting, limited by small sample sizes. Methods PubMed, Embase, Scopus, and Cochrane controlled register of trials (CENTRAL) were searched on ...
Ahmad A. Toubasi, Thuraya N. Al‐Sayegh
wiley +1 more source
This work investigates the application of remote sensing technologies within the specific operational context of emergency urban search and rescue (USAR) efforts post-disaster. We thoroughly investigate two innovative methodologies, each tailored to meet
Sivasakthy Selvakumaran +10 more
doaj +1 more source
In Search for a Pronatalist Population Policy for Turkey
Turkey has witnessed high fertility rates and low mortality rates until 2000s. Young population structure, need for infrastructure for growing population and reproductive health issues were always on the agenda of policy makers throughout the history of ...
Yusuf YÜKSEL
doaj +1 more source
Tracking and Mining the COVID-19 Research Literature
The unprecedented, explosive growth of the COVID-19 domain presents challenges to researchers to keep up with research knowledge within the domain. This article profiles this research to help make that knowledge more accessible via overviews and novel ...
Alan L. Porter +5 more
doaj +1 more source
Local Policy Search in a Convex Space and Conservative Policy Iteration as Boosted Policy Search [PDF]
Local Policy Search is a popular reinforcement learning approach for handling large state spaces. Formally, it searches locally in a parameterized policy space in order to maximize the associated value function averaged over some pre-defined distribution. The best one can hope in general from such an approach is to get a local optimum of this criterion.
Scherrer, Bruno, Geist, Matthieu
openaire +1 more source
Hierarchical Relative Entropy Policy Search [PDF]
Many reinforcement learning (RL) tasks, especially in robotics, consist of multiple sub-tasks that are strongly structured. Such task structures can be exploited by incorporating hierarchical policies that consist of gating networks and sub-policies.
C. Daniel +3 more
openaire +1 more source
Policy Search via the Signed Derivative [PDF]
We consider policy search for reinforcement learning: learning policy parameters, for some fixed policy class, that optimize performance of a system. In this paper, we propose a novel policy gradient method based on an approximation we call the Signed Derivative; the approximation is based on the intuition that it is often very easy to guess the ...
J. Z. Kolter, A. Y. Ng
openaire +1 more source
Turkey in Search of Relevant Foreign Policy Strategy (2002-2016)
The main idea of this article is to describe the process of Turkish foreign policy evolvement during the rule of Justice and Development party (JDP). From weak economy and unstable political situation in 2001, JDP quickly formulated a new strategy of ...
Urmanov Dayan R.
doaj +1 more source

