918 research outputs found
The Commerce Clause and Executive Power: Exploring \u3cem\u3eNascent Individual Rights in National Federal of Independent Business v. Sebelius\u3c/em\u3e (2012)
The Right to Same-Sex Marriage: Formalism, Realism, and Social Change in Lawrence (2003), Windsor (2013), & Obergefell (2015)
Originalism, the Living Constitution, and Supreme Court Decision Making in the Twenty-first Century: Explaining Lawrence v. Texas
\u27The Canon\u27 of Constitutional Law for Undergraduate Teaching: The Melding of Constitutional Theory, Law, and Interpretive/ Empirical Political Science
\u27The Canon\u27 of Constitutional Law for Undergraduate Teaching: The Melding of Constitutional Theory, Law, and Interpretive/ Empirical Political Science
Symposium: The Canon(s) of Constitutional La
Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning
Model-free deep reinforcement learning algorithms have been shown to be
capable of learning a wide range of robotic skills, but typically require a
very large number of samples to achieve good performance. Model-based
algorithms, in principle, can provide for much more efficient learning, but
have proven difficult to extend to expressive, high-capacity models such as
deep neural networks. In this work, we demonstrate that medium-sized neural
network models can in fact be combined with model predictive control (MPC) to
achieve excellent sample complexity in a model-based reinforcement learning
algorithm, producing stable and plausible gaits to accomplish various complex
locomotion tasks. We also propose using deep neural network dynamics models to
initialize a model-free learner, in order to combine the sample efficiency of
model-based approaches with the high task-specific performance of model-free
methods. We empirically demonstrate on MuJoCo locomotion tasks that our pure
model-based approach trained on just random action data can follow arbitrary
trajectories with excellent sample efficiency, and that our hybrid algorithm
can accelerate model-free learning on high-speed benchmark tasks, achieving
sample efficiency gains of 3-5x on swimmer, cheetah, hopper, and ant agents.
Videos can be found at https://sites.google.com/view/mbm
Knockout Mice Challenge our Concepts of Glucose Homeostasis and the Pathogenesis of Diabetes
A central component of type 2 diabetes and the metabolic
syndrome is insulin resistance. Insulin exerts a multifaceted
and highly integrated series of actions via its intracellular
signaling systems. Generation of mice carrying null mutations
of the genes encoding proteins in the insulin signaling
pathway provides a unique approach to determining the
role of individual proteins in the molecular mechanism of
insulin action and the pathogenesis of insulin resistance and
diabetes. The role of the four major insulin receptor substrates
(IRS1-4) in insulin and IGF-1 signaling have been
examined by creating mice with targeted gene knockouts.
Each produces a unique phenotype, indicating the complementary
role of these signaling components. Combined heterozygous
defects often produce synergistic or epistatic effects,
although the final severity of the phenotype depends
on the genetic background of the mice. Conditional knockouts
of the insulin receptor have also been created using the
Cre-lox system. These tissue specific knockouts have provide
unique insights into the control of glucose homeostasis
and the pathogenesis of type 2 diabetes, and have led to development
of new hypotheses about the nature of the insulin
action and development of diabetes
Comment: God Save Us from the Coercion Test: Constitutive Decisionmaking, Polity Principles, and Religious Freedom
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