Subscribe "Real life tends to cancel out." (Carroll's Razor)
James L. Carroll, "Computer Security for the LDS Family," Brigham Young Education Week Presentation, 2007.
James L. Carroll, "An Interpreters History of the Israelite Three
Room Temple Design," in The Ninth Annual BYU Religious Education Student Symposium, 2007.
In 1842, Joseph Smith revealed the endowment which connected the temple tradition with the creation and the Garden of Eden. Ancient Israel under the Law of Moses also built several temples. These temples were not primarily used for endowments as we understand them today, but were part of an Aaronic order designed to be preparatory in nature. These temples each contained three main rooms or divisions. We survey several of the most important LDS and non-LDS theories that attempt to explain the meaning of these rooms and show that even most non-LDS scholars believe that the Israelite temple design was connected with the creation, the Garden of Eden, and the fall of man. Thus, although these temples were not identical to the modern temple pattern revealed through the Endowment, they were designed to teach many of the same fundamental gospel principles. The majority of these scholarly opinions were given many years after Joseph revealed the Endowment, illustrating the inspiration of the prophet.
James L. Carroll, "Egyptian Craft Guild Initiations," in Studia Antiqua, The Journal of the Student
Society for Ancient Studies, 2007, vol. 5:1 p. 17-44.
Initiation seems to have played an important role in Egyptian religion from the beginning of recorded history. Initiations are rites whereby the initiate is symbolically moved from one state of being into another or from one part of the temple into another, the passage involves various trials or tests of knowledge, the rites often deal with death and resurrection, various oaths are taken either of an ethical or of a sacramental nature, and the ceremony itself is usually secret. The initiation paradigm can be seen in the Egyptian funerary literature, the Daily Temple Liturgy, the initiations of the Egyptian priesthood, and the later Isis mystery cult initiations. All these ritual elements can also be seen in modern craft guild initiations, however it is unclear how early this paradigm became part of craft guild initiations. Although it can be shown that craft guilds existed in ancient Egypt from the earliest times, little direct evidence of their nature has remained. However, several elements from the earlier Egyptian initiations show evidence of having been influenced by guild initiations. This indicates that the guild traditions may have adopted the initiation paradigm at a very early stage. If this is the case, then it would have significant ramifications for the origins of modern guild initiations, and would indicate that they are connected to ancient traditions of initiation into the afterlife, and to ancient temple traditions.
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James L. Carroll, "The Second
Coming of Christ as Covenant Renewal," in The Eighth Annual
BYU Religious Education Student Symposium, 2006.
The
second coming of Christ, especially his appearance at Jerusalem, can
be thought of as a covenant renewal ritual in which the people at
Jerusalem rediscover the identity of Jehovah, their God, and
recommit their lives to him. This covenant renewal ritual is
similar in form to the ancient covenant patterns found throughout
the ancient Near East and in the Old Testament accounts of Abraham
and Joshua. Viewing the second coming in this manner can help us to
understand several passages that would otherwise be difficult to
interpret, especially the division of the Mount of Olives. In this
context, the division of the Mount of Olives can be seen as a
re-creation of the sacred landscape that was present at Shechem when
the Israelites made their covenant with Jehovah before possessing
the Land of Promise.
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James L. Carroll, "A
Revised Temple Typology" in Hagion Temenos, 2nd
Edition ed. Stephen Ricks, Provo Ut. BYU Press, 2005.
John M. Lundquist's "Temple Typology" has been highly influential in the past several years. This "Revised Temple Typology" attempts to build upon what he has created by synthesizing several of Lundquist's publications and by adding several new elements to the typology. Further, the typology is reordered, and organized into three main categories, "the Temple Space," "The Temple Rites," and "The Tempe and Community." Short titles have also been added to the typology elements. It is hoped that these changes will improve the use of the typology in teaching situations.
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James L. Carroll, "An
Expanded View of the Israelite Scapegoat" in Selections
From the Seventh
Annual BYU Religious Education Student Symposium, 2005.
There have been many divergent interpretations of the scapegoat
in LDS and other Christian commentaries. Some see the scapegoat as a
symbol of Christ, others as a symbol of Satan. In order to better
understand the spiritual significance of the scapegoat, this paper
analyzes several scriptural stories that are similar in form to the
Day of Atonement, specifically stories where one person or group is
put to death, and another person or group is cast out or released.
It is then possible to understand the Lord's goat and the scapegoat
in terms of physical and spiritual death respectively. Such an
interpretation can explain how the scapegoat can represent the
Savior, who took spiritual death upon himself for those who repent,
while at the same time representing Satan, who was cast out of the
Father's presence, thus suffering spiritual death for his unrepented
sins.
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James L. Carroll, "The Reconciliation of Adam and Israelite
Temples," in Studia Antiqua, The Journal of the Student Society
for Ancient Studies, Winter 2003.
Modern researchers have shown that ancient temples were often
associated with the creation, the Garden of Eden, and
reconciliation. All three of these elements can be found in Genesis
1-3 if one assumes that Adam and Eve repented of their transgression
in the Garden as many apocryphal elements attest. The methods of
reconciliation that they record form a unifying principal for
understanding the significance of the tripartite divisions found in
Israelite temples which seem to have represented the heavenly throne
of God, the Garden of Eden, and the fallen world where Adam and Eve
worked out their reconciliation with God.
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A survey paper concerning the burning of Incense in its relation to the temple cult of Ancient Israel. We place the burning of incense in its contexts from the religions surrounding Israel, attempt to identify the ingredients mentioned in Ex. 30. We also survey various rabbinic commentaries on the methods for burning incense, and give an LDS interpretation for the meaning of this part of the ancient Israelite temple ritual.
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James L. Carroll, Robbie Haertel, Peter McClanahan, Eric Ringger, and Kevin Seppi,
"Modeling the Annotation Process for Ancient Corpus Creation," in ECAL Electronic corpora of ancient languages, Prague 2008.
In corpus creation human annotation is expensive. Annotation costs can be minimized through machine learning and active learning, however there are many complex interactions among the machine learner, the active learning technique, the annotation cost, human annotation accuracy, the annotator user interface, and several other elements of the process. For example, we show that changing the way in which annotators are paid can drastically change the performance of active learning techniques. To date these interactions have been poorly understood. We introduce a decision-theoretic model of the annotation process suitable for ancient corpus annotation that clarifies these interactions and can guide the development of a corpus creation project.
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James L. Carroll and Kevin D. Seppi, "No-Free-Lunch and Bayesian Optimality,"
in Meta-Learning IJCNN Workshop 2007.
We take a Bayesian approach to the issues of bias, meta
bias, transfer, overfit, and No-Free-Lunch in the context of
supervised learning. If we accept certain relationships between
the function class, on training set data, and off training
set data, then a graphical model can be created that
represents the supervised learning problem. This graphical
model dictates a specific algorithm which will be the “optimal”
approach to learning the parameters of any given
function representation given the variable relationships.
Thus, there is an optimal technique for supervised learning.
We reconcile this idea of an optimal technique with the
ideas of No-Free-Lunch and show how these ideas relate to
the concepts of meta and transfer learning through hierarchical
versions of the graphical model.
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James L. Carroll, Christopher K. Monson, and Kevin D. Seppi, "A Bayesian CMAC for
High Assurance Supervised Learning, in Applications of Neural Networks in
High-Assurance Systems, IJCNN Workshop 2007.
We analyze the drawbacks to using ANNs in
high assurance systems and propose a solution based upon
a Bayesian approach with a specific network topology that
can be solved in closed form. The Bayesian approach leads
to better answers in the traditional sense, while also allowing
us to quantify risk and deal with it in a reasonable manner. We
demonstrate this approach on several synthetic functions and
the Abalone data set.
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Eric Ringger, Peter McClanahan, Robbie Haertel, George Busby, Marc Carmen,
James Carroll, Kevin Seppi, Deryle Lonsdale, "Active Learning for Part-of-Speech
Tagging: Accelerating Corpus Annotation" in The 2007 Linguistic Annotation Workshop (LAW 2007).
In the construction of a part-of-speech annotated corpus, we are constrained by a
fixed budget. A fully annotated corpus is required, but we can afford to label only a
subset. We train a Maximum Entropy Markov Model tagger from a labeled subset
and automatically tag the remainder. This paper addresses the question of where to
focus our manual tagging efforts in order to deliver an annotation of highest quality. In
this context, we find that active learning is always helpful. We focus on Query by Uncertainty
(QBU) and Query by Committee (QBC) and report on experiments with several
baselines and new variations of QBC and QBU, inspired by weaknesses particular
to their use in this application. Experiments on English prose and poetry test
these approaches and evaluate their robustness. The results allow us to make recommendations
for both types of text and raise questions that will lead to further inquiry.
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Christopher K. Monson, Kevin D. Seppi, James L. Carroll,
"Utile Function Optimization," in The 2007 IEEE Congress of Evolutionary Computation (CEC 2007).
The Evolutionary Optimization DBN (EO-DBN)---a dynamic Bayesian model of optimization---provides a unique opportunity to create an algorithm that more directly addresses the goal of optimization: to carefully select function samples so as to obtain information about the location of its global optimum. As thus described, optimization is fundamentally a decision process and will therefore be addressed using the language and tools of decision theory. Having once cast the problem as a probabilistic network (the EO-DBN), it is possible to create a decision-making agent that uses explicit definitions of utility and cost to rationally select sample locations that maximize information. This work presents and develops this idea, producing a model of optimization and a corresponding algorithm that is optimal with respect to well-stated optimization goals. The algorithm uses naturally expressed domain knowledge to determine where a function should be sampled and when the sampling process should stop, displaying sophisticated behavior when provided with simple specifications.
James L. Carroll Task Localization, Similarity, and Transfer;
Towards a Reinforcement Learning Task Library System BYU Masters
Thesis, 2005.
This thesis develops methods of task localization, task
similarity discovery, and task transfer for eventual use in a
reinforcement learning task library system, which can effectively "learn
to learn," improving its performance as it encounters various tasks over
the lifetime of the learning system.
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James L. Carroll, Kevin Seppi "Task Similarity Measures for
Transfer in Reinforcement Learning Task Libraries" in The 2005 International Joint Conference on Neural Networks, (IJCNN 2005),
2005.
Recent research in task transfer and task clustering has
necessitated the need for task similarity measures in reinforcement
learning. Determining task similarity is necessary for selective
transfer where only information from relevant tasks and portions of a
task are transferred. Which task similarity measure to use is not
immediately obvious. It can be shown that no single task similarity
measure is uniformly superior. The optimal task similarity measure is
dependent upon the task transfer method being employed. We define
similarity in terms of tasks, and propose several possible task
similarity measures, dT , dP , dQ, and dR which are based on the
transfer time, policy overlap, Q-values, and reward structure
respectively. We evaluate their performance in three separate
experimental situations.
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James L. Carroll, Kevin Seppi "A Bayesian Technique for Task
Localization in Multiple Goal Markov Decision Processes," in The 2004 International Conference on Machine Learning and Applications, (ICMLA 2004).
In a reinforcement learning task library system for Multiple Goal
Markov Decision Process (MGMDP), localization in the task space allows
the agent to determine whether a given task is already in its library in
order to exploit previously learned experience. Task localization in
MGMDPs can be accomplished through a Bayesian approach, however a
trivial approach fails when the rewards are not distributed normally.
This can be overcome through our Bayesian Task Localization Technique (BTLT).
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James L. Carroll, Todd Peterson, Kevin Seppi "Reinforcement Learning
Task Clustering (RLTC)," in The 2003 International Conference on Machine Learning and Applications, (ICMLA 2003).
This work represents the first step towards a task library system in
the reinforcement learning domain. Task libraries could be useful in
speeding up the learning of new tasks through task transfer. Related
transfer can increase learning rate and can help prevent convergence to
sub-optimal policies in reinforcement learning. Unrelated transfer can
be extremely detrimental to the learning rate. Thus task transfer is
useful in reinforcement learning if the source task and the target task
are sufficiently related. Task similarity in reinforcement learning can
be determined using many different similarity metrics, and simple
clustering mechanisms can be applied to determine a set of related
tasks. Invariants can be determined among the set of related tasks and
then used in transfer. This paper uses information gathered from a set
of simple grid world tasks to show that clustering of tasks based upon a
similarity metric can be helpful in determining the set of source tasks
which should be utilized in transfer.
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James L. Carroll, Todd S. Peterson "Fixed vs. Dynamic Sub-transfer in
Reinforcement Learning," in The 2002 International Conference on Machine Learning and Applications,(ICMLA 2002).
We survey various task transfer methods in Q-learning and present a
variation on fixed sub-transfer which we call dynamic sub-transfer. We
discuss the benefits and drawbacks of dynamic sub-transfer as compared
with the other transfer methods, and we describe qualitatively the
situations where this method would be prefered over the fixed version of
sub-transfer. We test this method against several other transfer methods
in a simple three room grid world where portions of the source's policy
are relevant to the target task and other portions are not. In this
situation we found that dynamic sub-transfer converged to the optimal
solution, avoiding the sub-optimality inherent in fixed sub-transfer,
while also avoiding some of the convergence problems often experienced
by fixed sub-transfer.
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James L. Carroll, Todd S. Peterson, Nancy E. Owens, "Memory-guided
Exploration in Reinforcement Learning," in The 2001 International Joint Conference on Neural Networks, (IJCNN 2001).
The life-long learning architecture attempts to create an adaptive
agent through the incorporation of prior knowledge over the lifetime of
a learning agent. Our paper focuses on task transfer in reinforcement
learning and specifically in Q-learning. There are three main model free
methods for performing task transfer in Q-learning: direct transfer,
soft transfer and memory-guided exploration. In direct transfer Q-values
from a previous task are used to initialize the Q-values of the next
task. Soft transfer initializes the Q-values of the new task with a
weighted average of the standard initialization value and the Q-values
of the previous task. In memory-guided exploration the Q-values of
previous tasks are used as a guide in the initial exploration of the
agent. The weight that the agent gives to its past experience decreases
over time. We explore stability issues related to the off-policy nature
of memory-guided exploration and compare memory-guided exploration to
soft transfer and direct transfer in three different environments.
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Todd S. Peterson, Nancy E. Owens, and James L. Carroll, "Towards
Automatic Shaping in Robot Navigation," in The 2001 IEEE International Conference on Robotics
and Automation (ICRA, 2001).
Shaping is a potentially powerful tool in reinforcement learning
applications. Shaping often fails to function effectively because of a
lack of understanding about its effects when applied in reinforcement
learning settings and the use of inadequate algorithms in its
implementation. Because of these difficulties current shaping techniques
require some form of manual intervention. We examine some of the
principles involved in shaping and present a new algorithm for automatic
transferral of knowledge which uses Q-values established in a previous
task to guide exploration in the learning of a new task. This algorithm
is applied to two different but related robot navigation tasks.
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Physics:
Dr. J. Bart Czirr, David B. Merrill, David Buehler, Thomas K. McKnight, James L. Carroll, Thomas Abbott, Eva Wilcox, "Capture-gated Neutron Spectrometry," in Nuclear Instruments and Methods A, June 2000.