LIFE SUPPORT, SURROGATE AGENCY, DEEP LEARNING

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Criminal law has adopted the folk psychological view of human agency. Under this view, voluntary action exists and mental states, such as intentions, goals, and desires, have a causal relationship with bodily movement. However, new advances in neuroscience have begun to challenge this model and have lent empirical support to the idea that mental states may not play a causal role in bodily movement. This has profound implications for the voluntary act element of actus reus because the requirement presupposes the folk psychological view of agency. Nevertheless, criminal law can avoid this dilemma through praxeology, the deductive study of human action. This Article demonstrates through the deductive methods of praxeology that voluntary acts exist even assuming that mental states do not cause any bodily movement. Therefore, a praxeological conception of voluntariness in criminal law escapes the potential legal and bioethical dilemmas associated with using folk psychology in the voluntary act requirement. Furthermore, this Article shows that a praxeological theory of action is fully compatible with positive criminal law while still eliminating the possibility of legal voluntariness becoming a meaningless concept.

Extensive skill training using simulations for improving decision making has become a common practice in a multitude of domains and professions due to…

Publication - Deciding About Health Care: A Guide for Patients and Families

In this proof-of-concept work, we evaluate the performance of multiple machine-learning methods as surrogate models for use in the analysis of agent-based models (ABMs). Analysing agent-based modelling outputs can be challenging, as the relationships between input parameters can be non-linear or even chaotic even in relatively simple models, and each model run can require significant CPU time. Surrogate modelling, in which a statistical model of the ABM is constructed to facilitate detailed model analyses, has been proposed as an alternative to computationally costly Monte Carlo methods. Here we compare multiple machine-learning methods for ABM surrogate modelling in order to determine the approaches best suited as a surrogate for modelling the complex behaviour of ABMs. Our results suggest that, in most scenarios, artificial neural networks (ANNs) and gradient-boosted trees outperform Gaussian process surrogates, currently the most commonly used method for the surrogate modelling of complex computational models. ANNs produced the most accurate model replications in scenarios with high numbers of model runs, although training times were longer than the other methods. We propose that agent-based modelling would benefit from using machine-learning methods for surrogate modelling, as this can facilitate more robust sensitivity analyses for the models while also reducing CPU time consumption when calibrating and analysing the simulation.

Medicine, Health Care and Philosophy - In end-of-life care discussions, I contend that the distinction between “having a life” vs. “being alive” is an underutilized...

The Federal Select Agent Program oversees the possession, use and transfer of select agents and toxins, which pose a threat to public, animal or plant health.

Most older cancer patients received invasive care in the last month of their lives, a new study finds. That may not be what they wanted.

A Host of Possibilities was established in 2013 with a belief that a surrogacy agency’s relationship with you doesn’t end after they have been paid. We take the time to get to know every client and surrogate personally and professionally. Meet our team, and contact us for more. We look forward to meeting you!

Basic summaries and coherent overviews of omissions cases in criminal law.

In this paper, we propose surrogate agent-environment interface (SAEI) in reinforcement learning. We also state that learning based on probability surrogate agent-environment interface provides optimal policy of task agent-environment interface. We introduce surrogate probability action and develop the probability surrogate action deterministic policy gradient (PSADPG) algorithm based on SAEI. This algorithm enables continuous control of discrete action. The experiments show PSADPG achieves the performance of DQN in certain tasks with the stochastic optimal policy nature in the initial training stage.

The last days of life for patients with cancer involves managing end-of-life (EOL) care issues for a wide range of possible symptoms and ethical dilemmas. Get detailed information about EOL issues and the role of the oncologist in this clinician summary.

By Sander Hoog; Abstract: Abstract A very timely issue for economic agent-based models (ABMs) is their empirical estimation. This paper

Learn how medications can be used to treat substance use disorders, sustain recovery and prevent overdose.

Maeve Roughton asks if it’s becoming a crime to think the wrong thoughts.

Withdrawing or withholding invasive medical treatments to keep very ill patients in the ICU comfortable and communicative may not hasten their death.

Basic summaries and coherent overviews of causation cases in criminal law.