8 Search Results for "Miller, Mark S."


Document
Uncanny Valleys in Declarative Language Design

Authors: Mark S. Miller, Daniel von Dincklage, Vuk Ercegovac, and Brian Chin

Published in: LIPIcs, Volume 71, 2nd Summit on Advances in Programming Languages (SNAPL 2017)


Abstract
When people write programs in conventional programming languages, they over-specify how to solve the problem they have in mind. Over-specification prevents the language's implementation from making many optimization decisions, leaving programmers with this burden. In more declarative languages, programmers over-specify less, enabling the implementation to make more choices for them. As these decisions improve, programmers shift more attention from implementation to their real problems. This process easily overshoots. When under-specified programs almost always work well enough, programmers rarely need to think about implementation details. As their understanding of implementation choices atrophies, the controls provided so they can override these decisions become obscure. Our declarative language project, Yedalog, is in the midst of this dilemma. The improvements in question make our users more productive, so we cannot simply retreat back towards over-specification. To proceed forward instead, we must meet some of the expectations we prematurely provoked, and our implementation's behavior must help users learn expectations more aligned with our intended semantics. These are general issues. Discussing their concrete manifestation in Yedalog should help other declarative systems that come to face these issues.

Cite as

Mark S. Miller, Daniel von Dincklage, Vuk Ercegovac, and Brian Chin. Uncanny Valleys in Declarative Language Design. In 2nd Summit on Advances in Programming Languages (SNAPL 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 71, pp. 9:1-9:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)


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@InProceedings{miller_et_al:LIPIcs.SNAPL.2017.9,
  author =	{Miller, Mark S. and von Dincklage, Daniel and Ercegovac, Vuk and Chin, Brian},
  title =	{{Uncanny Valleys in Declarative Language Design}},
  booktitle =	{2nd Summit on Advances in Programming Languages (SNAPL 2017)},
  pages =	{9:1--9:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-032-3},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{71},
  editor =	{Lerner, Benjamin S. and Bod{\'\i}k, Rastislav and Krishnamurthi, Shriram},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.SNAPL.2017.9},
  URN =		{urn:nbn:de:0030-drops-71299},
  doi =		{10.4230/LIPIcs.SNAPL.2017.9},
  annote =	{Keywords: Declarative logic programming language}
}
Document
Trailer Brain: Neural and Behavioral Analysis of Social Issue Documentary Viewing with Low-Density EEG

Authors: Jason S. Sherwin, Corinne Brenner, and John S. Johnson

Published in: OASIcs, Volume 53, 7th Workshop on Computational Models of Narrative (CMN 2016)


Abstract
The effects of social issue documentaries are diverse. In particular, monetary donations and advocacy on social media are behavioral effects with public consequences. Conversely, information-seeking about an issue is potentially done in private. We designed a combined free-viewing and rapid perceptual decision-making experiment to simulate a real scenario confronted by otherwise uninformed movie-viewers, i.e., to determine what degree of support they will lend to a film based on its trailer. For a cohort of subjects with active video-streaming (e.g., Netflix) and social media accounts (e.g., Facebook), we recorded electroencephalography (EEG) and behavioral responses to trailers of social issue documentaries. We examined EEG using reliable component analysis (RCA), finding reliability within subjects across multiple viewings and across subjects within a given viewing of the same trailer. We found this reliability both over EEG captured from whole-movie viewing, as well as over 5-second movie segments. Behavioral responses following trailer viewing were not consistent from first to second viewings. Rather, support choices both tended towards extremes of support/non-support and were made faster upon second viewing. We hypothesized a relationship between reliability behavioral metrics, finding credible evidence for it in this dataset. Finally, we found that we could suitably train a naive classifier to categorize production value and narrative voice ratings given to the viewed movies from RCA-based metrics alone. In sum, our results show that EEG components during free-viewing of social issue documentary trailers can provide a useful tool to investigate viewers' neural responses during viewing, when coupled with a post hoc behavioral decision-making paradigm. The possibility of this tool being used by producers and filmmakers is also discussed.

Cite as

Jason S. Sherwin, Corinne Brenner, and John S. Johnson. Trailer Brain: Neural and Behavioral Analysis of Social Issue Documentary Viewing with Low-Density EEG. In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 2:1-2:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)


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@InProceedings{sherwin_et_al:OASIcs.CMN.2016.2,
  author =	{Sherwin, Jason S. and Brenner, Corinne and Johnson, John S.},
  title =	{{Trailer Brain: Neural and Behavioral Analysis of Social Issue Documentary Viewing with Low-Density EEG}},
  booktitle =	{7th Workshop on Computational Models of Narrative (CMN 2016)},
  pages =	{2:1--2:21},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-020-0},
  ISSN =	{2190-6807},
  year =	{2016},
  volume =	{53},
  editor =	{Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.2},
  URN =		{urn:nbn:de:0030-drops-67034},
  doi =		{10.4230/OASIcs.CMN.2016.2},
  annote =	{Keywords: EEG, reliable components analysis, machine learning, documentary films}
}
Document
Annotating Musical Theatre Plots on Narrative Structure and Emotional Content

Authors: Pablo Gervás, Raquel Hervás, Carlos León, and Catherine V. Gale

Published in: OASIcs, Volume 53, 7th Workshop on Computational Models of Narrative (CMN 2016)


Abstract
Although theoretical models of the structure of narrative arising from systematic analysis of corpora are available for domains such as Russian folk tales, there are no such sources for the plot lines of musical theatre. The present paper reports an effort of knowledge elicitation for features that characterise the narrative structure of plot in the particular domain of musical theatre. The following aspects are covered: identification of a valid vocabulary of abstract units to use in annotating musical theatre plots, development of a procedure for annotation - including a spread-sheet format for annotators to use, and a corresponding set of instructions to guide them through the process - selection of a corpus of musical theatre pieces that would constitute the corpus to be annotated, the annotation process itself and the results of post-processing the annotated corpus in search for insights on the narrative structure of musical theatre plots.

Cite as

Pablo Gervás, Raquel Hervás, Carlos León, and Catherine V. Gale. Annotating Musical Theatre Plots on Narrative Structure and Emotional Content. In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 11:1-11:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)


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@InProceedings{gervas_et_al:OASIcs.CMN.2016.11,
  author =	{Gerv\'{a}s, Pablo and Herv\'{a}s, Raquel and Le\'{o}n, Carlos and Gale, Catherine V.},
  title =	{{Annotating Musical Theatre Plots on Narrative Structure and Emotional Content}},
  booktitle =	{7th Workshop on Computational Models of Narrative (CMN 2016)},
  pages =	{11:1--11:16},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-020-0},
  ISSN =	{2190-6807},
  year =	{2016},
  volume =	{53},
  editor =	{Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.11},
  URN =		{urn:nbn:de:0030-drops-67122},
  doi =		{10.4230/OASIcs.CMN.2016.11},
  annote =	{Keywords: Narrative annotation, conceptual representation of narrative, character functions, narrative schemas, musical theatre}
}
Document
The Elements of Decision Alignment

Authors: Mark S. Miller and Bill Tulloh

Published in: LIPIcs, Volume 56, 30th European Conference on Object-Oriented Programming (ECOOP 2016)


Abstract
When one object makes a request of another, why do we expect that the second object's behavior correctly satisfies the first object's wishes? The need to cope with such principal-agent problems shapes programming practice as much as it shapes human organizations and economies. However, the literature about such plan coordination issues among humans is almost disjoint from the literature about these issues among objects. Even the terms used are unrelated. These fields have much to learn from each other---both from their similarities and from the causes of their differences. We propose a framework for thinking about decision alignment as a bridge between these disciplines.

Cite as

Mark S. Miller and Bill Tulloh. The Elements of Decision Alignment. In 30th European Conference on Object-Oriented Programming (ECOOP 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 56, pp. 17:1-17:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)


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@InProceedings{miller_et_al:LIPIcs.ECOOP.2016.17,
  author =	{Miller, Mark S. and Tulloh, Bill},
  title =	{{The Elements of Decision Alignment}},
  booktitle =	{30th European Conference on Object-Oriented Programming (ECOOP 2016)},
  pages =	{17:1--17:5},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-014-9},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{56},
  editor =	{Krishnamurthi, Shriram and Lerner, Benjamin S.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2016.17},
  URN =		{urn:nbn:de:0030-drops-61111},
  doi =		{10.4230/LIPIcs.ECOOP.2016.17},
  annote =	{Keywords: economics, law, contracts, principal-agent problem, incentive alignment, least authority, verification}
}
Document
From Episodic Memory to Narrative in a Cognitive Architecture

Authors: Tory S. Anderson

Published in: OASIcs, Volume 45, 6th Workshop on Computational Models of Narrative (CMN 2015)


Abstract
Human experiences are stored in episodic memory and are the basis for developing semantic narrative structures and many of the narratives we continually compose. Episodic memory has only recently been recognized as a necessary module in general cognitive architectures and little work has been done to examine how the data stored by these modules may be formulated as narrative structures. This paper regards episodic memory as fundamental to narrative intelligence and considers the gap between simple episodic memory representations and narrative structures, and proposes an approach to generating basic narratives from episodic sequences. An approach is outlined considering the Soar general cognitive architecture and Zacks’ Event Segmentation Theory.

Cite as

Tory S. Anderson. From Episodic Memory to Narrative in a Cognitive Architecture. In 6th Workshop on Computational Models of Narrative (CMN 2015). Open Access Series in Informatics (OASIcs), Volume 45, pp. 2-11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)


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@InProceedings{anderson:OASIcs.CMN.2015.2,
  author =	{Anderson, Tory S.},
  title =	{{From Episodic Memory to Narrative in a Cognitive Architecture}},
  booktitle =	{6th Workshop on Computational Models of Narrative (CMN 2015)},
  pages =	{2--11},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-93-4},
  ISSN =	{2190-6807},
  year =	{2015},
  volume =	{45},
  editor =	{Finlayson, Mark A. and Miller, Ben and Lieto, Antonio and Ronfard, Remi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2015.2},
  URN =		{urn:nbn:de:0030-drops-52761},
  doi =		{10.4230/OASIcs.CMN.2015.2},
  annote =	{Keywords: Narrative, Episodic Memory, Cognitive Architecture, Event Segmentation}
}
Document
Schemas for Narrative Generation Mined from Existing Descriptions of Plot

Authors: Pablo Gervás, Carlos León, and Gonzalo Méndez

Published in: OASIcs, Volume 45, 6th Workshop on Computational Models of Narrative (CMN 2015)


Abstract
Computational generation of literary artifacts very often resorts to template-like schemas that can be instantiated into complex structures. With this view in mind, the present paper reviews a number of existing attempts to provide an elementary set of patterns for basic plots. An attempt is made to formulate these descriptions of possible plots in terms of character functions, an abstraction of plot-bearing elements of a story originally formulated by Vladimir Propp. These character functions act as the building blocks of the Propper system, an existing framework for computational story generation. The paper explores the set of extensions required to the original set of character functions to allow for a basic representation of the analysed schemata, and a solution for automatic generation of stories based on this formulation of the narrative schemas. This solution uncovers important insights on the relative expressive power of the representation of narrative in terms of character functions, and their impact on the generative potential of the framework is discussed.

Cite as

Pablo Gervás, Carlos León, and Gonzalo Méndez. Schemas for Narrative Generation Mined from Existing Descriptions of Plot. In 6th Workshop on Computational Models of Narrative (CMN 2015). Open Access Series in Informatics (OASIcs), Volume 45, pp. 54-71, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)


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@InProceedings{gervas_et_al:OASIcs.CMN.2015.54,
  author =	{Gerv\'{a}s, Pablo and Le\'{o}n, Carlos and M\'{e}ndez, Gonzalo},
  title =	{{Schemas for Narrative Generation Mined from Existing Descriptions of Plot}},
  booktitle =	{6th Workshop on Computational Models of Narrative (CMN 2015)},
  pages =	{54--71},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-93-4},
  ISSN =	{2190-6807},
  year =	{2015},
  volume =	{45},
  editor =	{Finlayson, Mark A. and Miller, Ben and Lieto, Antonio and Ronfard, Remi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2015.54},
  URN =		{urn:nbn:de:0030-drops-52812},
  doi =		{10.4230/OASIcs.CMN.2015.54},
  annote =	{Keywords: Narrative generation, conceptual representation of narrative, character functions, plot, narrative schemas}
}
Document
The Love Equation: Computational Modeling of Romantic Relationships in French Classical Drama

Authors: Folgert Karsdorp, Mike Kestemont, Christof Schöch, and Antal van den Bosch

Published in: OASIcs, Volume 45, 6th Workshop on Computational Models of Narrative (CMN 2015)


Abstract
We report on building a computational model of romantic relationships in a corpus of historical literary texts. We frame this task as a ranking problem in which, for a given character, we try to assign the highest rank to the character with whom (s)he is most likely to be romantically involved. As data we use a publicly available corpus of French 17th and 18th century plays (http://www.theatre-classique.fr/) which is well suited for this type of analysis because of the rich markup it provides (e.g. indications of characters speaking). We focus on distributional, so-called second-order features, which capture how speakers are contextually embedded in the texts. At a mean reciprocal rate (MRR) of 0.9 and MRR@1 of 0.81, our results are encouraging, suggesting that this approach might be successfully extended to other forms of social interactions in literature, such as antagonism or social power relations.

Cite as

Folgert Karsdorp, Mike Kestemont, Christof Schöch, and Antal van den Bosch. The Love Equation: Computational Modeling of Romantic Relationships in French Classical Drama. In 6th Workshop on Computational Models of Narrative (CMN 2015). Open Access Series in Informatics (OASIcs), Volume 45, pp. 98-107, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)


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@InProceedings{karsdorp_et_al:OASIcs.CMN.2015.98,
  author =	{Karsdorp, Folgert and Kestemont, Mike and Sch\"{o}ch, Christof and van den Bosch, Antal},
  title =	{{The Love Equation: Computational Modeling of Romantic Relationships in French Classical Drama}},
  booktitle =	{6th Workshop on Computational Models of Narrative (CMN 2015)},
  pages =	{98--107},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-93-4},
  ISSN =	{2190-6807},
  year =	{2015},
  volume =	{45},
  editor =	{Finlayson, Mark A. and Miller, Ben and Lieto, Antonio and Ronfard, Remi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2015.98},
  URN =		{urn:nbn:de:0030-drops-52838},
  doi =		{10.4230/OASIcs.CMN.2015.98},
  annote =	{Keywords: French drama, social relations, neural network, representation learning}
}
Document
Yedalog: Exploring Knowledge at Scale

Authors: Brian Chin, Daniel von Dincklage, Vuk Ercegovac, Peter Hawkins, Mark S. Miller, Franz Och, Christopher Olston, and Fernando Pereira

Published in: LIPIcs, Volume 32, 1st Summit on Advances in Programming Languages (SNAPL 2015)


Abstract
With huge progress on data processing frameworks, human programmers are frequently the bottleneck when analyzing large repositories of data. We introduce Yedalog, a declarative programming language that allows programmers to mix data-parallel pipelines and computation seamlessly in a single language. By contrast, most existing tools for data-parallel computation embed a sublanguage of data-parallel pipelines in a general-purpose language, or vice versa. Yedalog extends Datalog, incorporating not only computational features from logic programming, but also features for working with data structured as nested records. Yedalog programs can run both on a single machine, and distributed across a cluster in batch and interactive modes, allowing programmers to mix different modes of execution easily.

Cite as

Brian Chin, Daniel von Dincklage, Vuk Ercegovac, Peter Hawkins, Mark S. Miller, Franz Och, Christopher Olston, and Fernando Pereira. Yedalog: Exploring Knowledge at Scale. In 1st Summit on Advances in Programming Languages (SNAPL 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 32, pp. 63-78, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)


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@InProceedings{chin_et_al:LIPIcs.SNAPL.2015.63,
  author =	{Chin, Brian and von Dincklage, Daniel and Ercegovac, Vuk and Hawkins, Peter and Miller, Mark S. and Och, Franz and Olston, Christopher and Pereira, Fernando},
  title =	{{Yedalog: Exploring Knowledge at Scale}},
  booktitle =	{1st Summit on Advances in Programming Languages (SNAPL 2015)},
  pages =	{63--78},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-80-4},
  ISSN =	{1868-8969},
  year =	{2015},
  volume =	{32},
  editor =	{Ball, Thomas and Bodík, Rastislav and Krishnamurthi, Shriram and Lerner, Benjamin S. and Morriset, Greg},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.SNAPL.2015.63},
  URN =		{urn:nbn:de:0030-drops-50172},
  doi =		{10.4230/LIPIcs.SNAPL.2015.63},
  annote =	{Keywords: Datalog, MapReduce}
}
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