130,189 research outputs found
Nonperturbative results for the mass dependence of the QED fermion determinant
The fermion determinant in four-dimensional quantum electrodynamics in the
presence of O(2)XO(3) symmetric background gauge fields with a nonvanishing
global chiral anomaly is considered. It is shown that the leading mass
singularity of the determinant's nonperturbative part is fixed by the anomaly.
It is also shown that for a large class of such fields there is at least one
value of the fermion mass at which the determinant's nonperturbative part
reduces to its noninteracting value.Comment: This is an extended version of the author's paper in
Phys.Rev.D81(2010)10770
Learning to Play Othello with N-Tuple Systems
This paper investigates the use of n-tuple systems as position value functions for the game of Othello. The architecture is described, and then evaluated for use with temporal difference learning. Performance is compared with previously de-veloped weighted piece counters and multi-layer perceptrons. The n-tuple system is able to defeat the best performing of these after just five hundred games of self-play learning. The conclusion is that n-tuple networks learn faster and better than the other more conventional approaches
The Problem of Analogical Inference in Inductive Logic
We consider one problem that was largely left open by Rudolf Carnap in his
work on inductive logic, the problem of analogical inference. After discussing
some previous attempts to solve this problem, we propose a new solution that is
based on the ideas of Bruno de Finetti on probabilistic symmetries. We explain
how our new inductive logic can be developed within the Carnapian paradigm of
inductive logic-deriving an inductive rule from a set of simple postulates
about the observational process-and discuss some of its properties.Comment: In Proceedings TARK 2015, arXiv:1606.0729
Navigating Troubled Waters: Dealing with Personal Values When Representing Others
Legal academics have long struggled to define the appropriate role a lawyer\u27s moral judgment ought to play in client representation. In its simplest terms, the question is: Must a lawyer be a hired gun, seeking all lawful objectives sought by a client, or may a lawyer act independently to avoid the harm a client\u27s actions will cause innocent parties? Following disclosure of lawyer involvement in the Savings and Loan, Enron and WorldCom failures, many in society joined those scholars calling for greater moral responsibility.
In this article, I provide an analytical approach consistent with existing law and practice that seeks to find a place for an individual lawyer\u27s moral principles. Lawyers, particularly new lawyers, need to know just how much discretion they will have to follow their consciences. Understanding the limits on one\u27s moral discretion will affect the way a lawyer practices and should influence her choice of practice environment. Prior to accepting a position, a lawyer should know whether she will be comfortable with the prevailing standards of practice
Introduction to a Resources Special Issue on Criticality of the Rare Earth Elements: Current and Future Sources and Recycling
The rare earth elements (REE) are vital to modern technologies and society and are amongst the most important of the critical elements. This special issue of Resources examines a number of facets of these critical elements, current and future sources of the REE, the mineralogy of the REE, and the economics of the REE sector. These papers not only provide insights into a wide variety of aspects of the REE, but also highlight the number of different areas of research that need to be undertaken to ensure sustainable and secure supplies of these critical metals into the future
Temporal difference learning with interpolated table value functions
This paper introduces a novel function approximation architecture especially well suited to temporal difference learning. The architecture is based on using sets of interpolated table look-up functions. These offer rapid and stable learning, and are efficient when the number of inputs is small. An empirical investigation is conducted to test their performance on a supervised learning task, and on themountain car problem, a standard reinforcement learning benchmark. In each case, the interpolated table functions offer competitive performance. ©2009 IEEE
Investigating learning rates for evolution and temporal difference learning
Evidently, any learning algorithm can only learn on the basis of the information given to it. This paper presents a first attempt to place an upper bound on the information rates attainable with standard co-evolution and with TDL. The upper bound for TDL is shown to be much higher than for coevolution. Under commonly used settings for learning to play Othello for example, TDL may have an upper bound that is hundreds or even thousands of times higher than that of coevolution. To test how well these bounds correlate with actual learning rates, a simple two-player game called Treasure Hunt. is developed. While the upper bounds cannot be used to predict the number of games required to learn the optimal policy, they do correctly predict the rank order of the number of games required by each algorithm. © 2008 IEEE
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