Commit 241956f9bb8224fb6e8b759f89a14ad8b2b48b68
1 parent
b43c061c
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continuing 00_PASP
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text/00_PASP.aux
| ... | ... | @@ -45,121 +45,130 @@ |
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text/00_PASP.fdb_latexmk
| 1 | 1 | # Fdb version 3 |
| 2 | -["xdvipdfmx"] 1667928801 "00_PASP.xdv" "00_PASP.pdf" "00_PASP" 1667928802 | |
| 3 | - "00_PASP.xdv" 1667928801 200932 982c61eac8b5d4d97d7ddad987e569ae "xelatex" | |
| 2 | +["xdvipdfmx"] 1667935664 "00_PASP.xdv" "00_PASP.pdf" "00_PASP" 1667935664 | |
| 3 | + "00_PASP.xdv" 1667935663 214680 71a3fe8c0e42560f8631e0d09f4181a7 "xelatex" | |
| 4 | 4 | (generated) |
| 5 | 5 | "00_PASP.pdf" |
| 6 | -["xelatex"] 1667928794 "/home/fc/sci/projetos/zugzwang/text/00_PASP.tex" "00_PASP.xdv" "00_PASP" 1667928802 | |
| 7 | - "/home/fc/sci/projetos/zugzwang/text/00_PASP.tex" 1667928794 29667 8d68ac0db717033678db2dd1c81ee58c "" | |
| 6 | +["xelatex"] 1667935657 "/home/fc/sci/projetos/zugzwang/text/00_PASP.tex" "00_PASP.xdv" "00_PASP" 1667935664 | |
| 7 | + "/home/fc/sci/projetos/zugzwang/text/00_PASP.tex" 1667935656 32020 e7e67df128d9c518e87afbb7c6491ef3 "" | |
| 8 | 8 | "/usr/share/texmf-dist/fonts/map/fontname/texfonts.map" 1650183167 3524 cb3e574dea2d1052e39280babc910dc8 "" |
| 9 | 9 | "/usr/share/texmf-dist/fonts/tfm/adobe/zapfding/pzdr.tfm" 1650183167 1528 f853c4d1b4e0550255e02831fdc8496f "" |
| 10 | 10 | "/usr/share/texmf-dist/fonts/tfm/public/amsfonts/cmextra/cmex7.tfm" 1650183167 1004 54797486969f23fa377b128694d548df "" |
| ... | ... | @@ -226,11 +226,11 @@ |
| 226 | 226 | "/usr/share/texmf-dist/tex/latex/xcolor/xcolor.sty" 1650183167 56029 3f7889dab51d620aa43177c391b7b190 "" |
| 227 | 227 | "/usr/share/texmf-dist/web2c/texmf.cnf" 1650183167 39911 2da6c67557ec033436fe5418a70a8a61 "" |
| 228 | 228 | "/var/lib/texmf/web2c/xetex/xelatex.fmt" 1667607223 5825155 acc75abcaf8e6f881414fa8770610f6c "" |
| 229 | - "00_PASP.aux" 1667928801 9634 8e144a491304a1dcf0003771d7f89fb7 "xelatex" | |
| 230 | - "00_PASP.nav" 1667928801 4276 4edecfe6ebd3d4b2e818cd376272e5e4 "xelatex" | |
| 231 | - "00_PASP.out" 1667928801 1097 fd2c5e9a9165683b5658636d6bb611e1 "xelatex" | |
| 232 | - "00_PASP.tex" 1667928794 29667 8d68ac0db717033678db2dd1c81ee58c "" | |
| 233 | - "00_PASP.toc" 1667928801 383 bceb83a7e3f28815a9defb8c90b2016a "xelatex" | |
| 229 | + "00_PASP.aux" 1667935663 10150 06d1cb9804fa13f9caa5b87bee738349 "xelatex" | |
| 230 | + "00_PASP.nav" 1667935663 4557 bd5b660e37644e87cd38eeeceb472239 "xelatex" | |
| 231 | + "00_PASP.out" 1667935663 1097 ff89349dbd8e3874420c8d8c57eb7504 "xelatex" | |
| 232 | + "00_PASP.tex" 1667935656 32020 e7e67df128d9c518e87afbb7c6491ef3 "" | |
| 233 | + "00_PASP.toc" 1667935663 384 d39373a67753c9668ace5a0f122dc338 "xelatex" | |
| 234 | 234 | "Pabc_alpha03.pdf" 1663331875 12659 e50124c327299028f63ecb501d23eb0d "" |
| 235 | 235 | (generated) |
| 236 | 236 | "00_PASP.aux" | ... | ... |
text/00_PASP.fls
| ... | ... | @@ -1467,11 +1467,11 @@ INPUT /usr/share/texmf-dist/fonts/tfm/public/lm/ec-lmss8.tfm |
| 1467 | 1467 | INPUT /usr/share/texmf-dist/fonts/tfm/public/lm/ec-lmsso10.tfm |
| 1468 | 1468 | INPUT /usr/share/texmf-dist/fonts/tfm/public/lm/ec-lmsso8.tfm |
| 1469 | 1469 | INPUT /usr/share/texmf-dist/fonts/tfm/public/lm/ec-lmsso8.tfm |
| 1470 | -INPUT /usr/share/texmf-dist/fonts/tfm/public/lm/ec-lmssbo10.tfm | |
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text/00_PASP.out
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text/00_PASP.pdf
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text/00_PASP.snm
| 1 | 1 | \beamer@slide {eq:prob.tc}{5} |
| 2 | 2 | \beamer@slide {prop:unique.ext.tcsm}{7} |
| 3 | -\beamer@slide {prop:lucases}{11} | |
| 4 | -\beamer@slide {prop:lucases.a}{11} | |
| 5 | -\beamer@slide {prop:lucases.b}{11} | |
| 6 | -\beamer@slide {prop:lucases.c}{11} | |
| 7 | -\beamer@slide {prop:lucases.d}{11} | |
| 8 | -\beamer@slide {def:w.inconsistent}{13} | |
| 9 | -\beamer@slide {eq:prob.sm}{13} | |
| 10 | -\beamer@slide {def:w.disj}{13} | |
| 11 | -\beamer@slide {def:w.conj}{13} | |
| 12 | -\beamer@slide {def:w.empty}{13} | |
| 13 | -\beamer@slide {eq:def.prob}{13} | |
| 14 | -\beamer@slide {eq:def.prob.event}{13} | |
| 3 | +\beamer@slide {prop:lucases}{14} | |
| 4 | +\beamer@slide {prop:lucases.a}{14} | |
| 5 | +\beamer@slide {prop:lucases.b}{14} | |
| 6 | +\beamer@slide {prop:lucases.c}{14} | |
| 7 | +\beamer@slide {prop:lucases.d}{14} | |
| 8 | +\beamer@slide {def:w.inconsistent}{16} | |
| 9 | +\beamer@slide {eq:prob.sm}{16} | |
| 10 | +\beamer@slide {def:w.disj}{16} | |
| 11 | +\beamer@slide {def:w.conj}{16} | |
| 12 | +\beamer@slide {def:w.empty}{16} | |
| 13 | +\beamer@slide {eq:def.prob}{16} | |
| 14 | +\beamer@slide {eq:def.prob.event}{16} | ... | ... |
text/00_PASP.synctex.gz
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text/00_PASP.tex
| ... | ... | @@ -49,6 +49,7 @@ |
| 49 | 49 | \newcommand{\uset}[1]{\ensuremath{\left|{#1}\right>}} |
| 50 | 50 | \newcommand{\lset}[1]{\ensuremath{\left<{#1}\right|}} |
| 51 | 51 | \newcommand{\pr}[1]{\ensuremath{\mathrm{p}\at{#1}}} |
| 52 | +\newcommand{\given}{\ensuremath{~\middle|~}} | |
| 52 | 53 | % |
| 53 | 54 | % Identificaรงรฃo deste documento |
| 54 | 55 | % |
| ... | ... | @@ -95,10 +96,10 @@ |
| 95 | 96 | \item \textbf{Atoms} $\fml{A}$, |
| 96 | 97 | $\overline{\fml{A}} = \cset{\neg a}{a \in \fml{A}}$, |
| 97 | 98 | % -------------------------------- |
| 98 | - \item \textbf{Observations} $\fml{Z}$: | |
| 99 | + \item \textbf{Inputs} $\fml{Z}$: | |
| 99 | 100 | $$\fml{Z} = \cset{z = \alpha \cup \beta }{ \alpha \subseteq \fml{A} \land \beta \subseteq \overline{\fml{A}} }$$ |
| 100 | 101 | % -------------------------------- |
| 101 | - \item \textbf{Interpretations} or \textit{consistent observations} $\fml{I}$ : | |
| 102 | + \item \textbf{Interpretations} or \textit{consistent inputs} $\fml{I}$ : | |
| 102 | 103 | $$\fml{I} = \cset{z \in \fml{Z} }{ \forall a \in \fml{A}~\envert{\set{a,\neg a} \cap z} \leq 1}.$$ |
| 103 | 104 | % -------------------------------- |
| 104 | 105 | \item \textit{PASP Problem} or \textbf{Specification:} $P = C \land F \land R$ where |
| ... | ... | @@ -111,7 +112,7 @@ |
| 111 | 112 | % -------------------------------- |
| 112 | 113 | \item $R = R_P$ \textit{rules}. |
| 113 | 114 | % -------------------------------- |
| 114 | - \item $\fml{A}_P, \fml{Z}_P$ and $\fml{I}_P$: \textit{atoms}, \textit{observations} and \textit{interpretations} of $P$. | |
| 115 | + \item $\fml{A}_P, \fml{Z}_P$ and $\fml{I}_P$: \textit{atoms}, \textit{inputs} and \textit{interpretations} of $P$. | |
| 115 | 116 | \end{itemize} |
| 116 | 117 | % -------------------------------- |
| 117 | 118 | \item \textbf{Stable Models} of $P$, $\fml{S} = \fml{S}_P$, are the stable models of $\delta P = \delta C + F + R$. |
| ... | ... | @@ -124,7 +125,7 @@ |
| 124 | 125 | % -------------------------------- |
| 125 | 126 | \begin{itemize} |
| 126 | 127 | % -------------------------------- |
| 127 | - \item \textbf{Total Choices:} $\Theta = \Theta_C = \Theta_P$ elements are $\theta = \set{c_1, \ldots, c_n}$ where $c_i$ is $a_i$ or $\neg a_i$. | |
| 128 | + \item \textbf{Total Choices:} $\Theta = \Theta_C = \Theta_P$ elements are $\theta = \cset{t_c}{c \in C}$ where $c=\alpha::a$ and $t_c$ is $a$ or $\neg a$. | |
| 128 | 129 | % -------------------------------- |
| 129 | 130 | %\item For $s\in\fml{S}$ let $\theta_s \subseteq s$ (unique \textit{total choice}) |
| 130 | 131 | %\item Define $\fml{S}_\theta = \cset{s \in \fml{S}}{\theta \subset s}$. |
| ... | ... | @@ -133,30 +134,20 @@ |
| 133 | 134 | % -------------------------------- |
| 134 | 135 | \item \textbf{Total Choice Probability:} |
| 135 | 136 | \begin{equation} |
| 136 | - \pr{\theta} = \prod_{a_i \in \theta}\alpha_i \prod_{\neg a_i \in \theta}\co{\alpha_i}.\label{eq:prob.tc} | |
| 137 | + \pr{\theta} = \prod_{a \in \theta}\alpha \prod_{\neg a \in \theta}\co{\alpha}.\label{eq:prob.tc} | |
| 137 | 138 | \end{equation} |
| 138 | 139 | % -------------------------------- |
| 139 | 140 | \end{itemize} |
| 140 | 141 | % -------------------------------- |
| 141 | - \begin{quote} | |
| 142 | - This is the \emph{Distribution Semantics} as set by Sato. | |
| 143 | - \end{quote} | |
| 142 | + This is the \emph{distribution semantic} as set by Sato. | |
| 144 | 143 | \end{frame} |
| 145 | 144 | % ================================================================ |
| 146 | 145 | \begin{frame}{Problem Statement} |
| 147 | 146 | % -------------------------------- |
| 148 | - \begin{quotation} | |
| 149 | - How to extend probability from the total choices to interpretations and observations? | |
| 150 | - \end{quotation} | |
| 151 | - % -------------------------------- | |
| 152 | - \begin{itemize} | |
| 153 | - % -------------------------------- | |
| 154 | - \item \textbf{Todo:} Extend probability to \textit{stable models}, \textit{interpretations} and \textit{observations}. | |
| 155 | - % -------------------------------- | |
| 156 | - \end{itemize} | |
| 147 | + How to \textit{extend} probability from total choices to stable models, interpretations and inputs? | |
| 157 | 148 | % -------------------------------- |
| 158 | 149 | \begin{quotation} |
| 159 | - \textbf{But} there is a problem extending probability from total choices to stable models. | |
| 150 | + There's a problem right at extending to stable models. | |
| 160 | 151 | \end{quotation} |
| 161 | 152 | % -------------------------------- |
| 162 | 153 | \end{frame} |
| ... | ... | @@ -200,32 +191,96 @@ |
| 200 | 191 | % -------------------------------- |
| 201 | 192 | \end{frame} |
| 202 | 193 | % ================================================================ |
| 194 | +\begin{frame}{Lack of Information \& Parametrization} | |
| 195 | + % -------------------------------- | |
| 196 | + \begin{itemize} | |
| 197 | + % -------------------------------- | |
| 198 | + \item The specification \textit{lacks information} to set $\alpha\in\intcc{0,1}$ in | |
| 199 | + $$ | |
| 200 | + \begin{aligned} | |
| 201 | + \pr{\set{a, b}} &= 0.3 \alpha, \cr | |
| 202 | + \pr{\set{a, c}} &= 0.3 \co{\alpha}. | |
| 203 | + \end{aligned} | |
| 204 | + $$ | |
| 205 | + \item A \textit{random variable} captures this: | |
| 206 | + $$ | |
| 207 | + \begin{aligned} | |
| 208 | + \pr{\set{\neg a} \given\ A = \alpha } &= 0.7, \cr | |
| 209 | + \pr{\set{a, b} \given\ A = \alpha } &= 0.3 \alpha, \cr | |
| 210 | + \pr{\set{a, c} \given\ A = \alpha } &= 0.3 \co{\alpha}. | |
| 211 | + \end{aligned} | |
| 212 | + $$ | |
| 213 | + \item Other uncertainties lead to further parameters: | |
| 214 | + $$ | |
| 215 | + \pr{s \given\ A_1 = \alpha_1, \ldots, A_n = \alpha_n }. | |
| 216 | + $$ | |
| 217 | + % -------------------------------- | |
| 218 | + \end{itemize} | |
| 219 | + Reducing \textbf{specification uncertainty}, \textit{e.g.} setting $A = 0.21$, must result from \textbf{observations}. | |
| 220 | + % -------------------------------- | |
| 221 | +\end{frame} | |
| 222 | +% ================================================================ | |
| 223 | +\begin{frame}{Main Research Question} | |
| 224 | + % -------------------------------- | |
| 225 | + A \textit{random variable} captures this: | |
| 226 | + $$ | |
| 227 | + \begin{aligned} | |
| 228 | + \pr{\set{\neg a} \given\ A = \alpha } &= 0.7, \cr | |
| 229 | + \pr{\set{a, b} \given\ A = \alpha } &= 0.3 \alpha, \cr | |
| 230 | + \pr{\set{a, c} \given\ A = \alpha } &= 0.3 \co{\alpha}. | |
| 231 | + \end{aligned} | |
| 232 | + $$ | |
| 233 | + % -------------------------------- | |
| 234 | + \begin{block}{Main Research Question} | |
| 235 | + Can \textit{all} specification uncertainties be neatly expressed as that example? | |
| 236 | + \end{block} | |
| 237 | + % -------------------------------- | |
| 238 | + \begin{itemize} | |
| 239 | + % -------------------------------- | |
| 240 | + \item Follow ASP syntax; for each case, consider the possible uncertainty scenarios. | |
| 241 | + % -------------------------------- | |
| 242 | + \item The disjunction example illustrates one such step. | |
| 243 | + % -------------------------------- | |
| 244 | + \end{itemize} | |
| 245 | + % -------------------------------- | |
| 246 | +\end{frame} | |
| 247 | +% ================================================================ | |
| 203 | 248 | \section{Motivation} |
| 204 | 249 | % ================================================================ |
| 205 | 250 | \begin{frame}{Specification, Data \& Evaluation} |
| 206 | 251 | % -------------------------------- |
| 207 | - Given some procedure to assign probabilities to observations from specifications and: | |
| 252 | + Given some procedure to extend probabilities to stable models, interpretations and inputs, and given: | |
| 208 | 253 | % -------------------------------- |
| 209 | 254 | \begin{itemize} |
| 210 | 255 | % -------------------------------- |
| 211 | 256 | \item $P$, a specification. |
| 212 | 257 | % -------------------------------- |
| 213 | - \item $p$, the distribution of observations from above. | |
| 258 | + \item $p$, the distribution of inputs from above. | |
| 214 | 259 | % -------------------------------- |
| 215 | - \item $Z$, a dataset of observations. | |
| 260 | + \item $Z$, a dataset of inputs. | |
| 216 | 261 | % -------------------------------- |
| 217 | 262 | \item $e$, the respective empirical distribution. |
| 218 | 263 | % -------------------------------- |
| 219 | 264 | \item $D$, some probability divergence, \textit{e.g.} Kullback-Leibler. |
| 220 | 265 | % -------------------------------- |
| 221 | 266 | \end{itemize} |
| 222 | - % -------------------------------- | |
| 223 | - Given a dataset $Z$, $D\at{P} = D\at{e, p}$ is a \textit{performance} measure of $P$ and can be used, \textit{e.g.} fitness, by algorithms searching for optimal specifications of a dataset. | |
| 267 | + % -------------------------------- | |
| 268 | + \begin{quotation} | |
| 269 | + For a dataset $Z$, $D\at{P} = D\at{e, p}$ is a \textbf{performance} measure of $P$ and can be used, \textit{e.g.} as fitness, by algorithms searching for \textbf{optimal specifications of a dataset}. | |
| 270 | + \end{quotation} | |
| 224 | 271 | % -------------------------------- |
| 225 | 272 | \end{frame} |
| 226 | 273 | % ================================================================ |
| 227 | 274 | \section{Resolution} |
| 228 | 275 | % ================================================================ |
| 276 | +\begin{frame}{Resolution Path} | |
| 277 | + \begin{enumerate} | |
| 278 | + \item \textit{Parametrize} lack of knowledge \emph{e.g.} $\alpha$ in the disjunction example. | |
| 279 | + \item This extends probability from total choices to \textit{standard models}. | |
| 280 | + \item Extend probability from standard models to \textit{interpretations}. \textbf{How?} Later. | |
| 281 | + \item Set $\pr{z} = 0$ for $z \in \fml{Z} \setminus \fml{I}$. | |
| 282 | + \end{enumerate} | |
| 283 | +\end{frame} | |
| 229 | 284 | \begin{frame}{Bounds of Interpretations} |
| 230 | 285 | % -------------------------------- |
| 231 | 286 | \begin{itemize} |
| ... | ... | @@ -294,9 +349,9 @@ |
| 294 | 349 | \end{equation} |
| 295 | 350 | \end{enumerate} |
| 296 | 351 | % |
| 297 | - \item The last point defines a ``weight'' function on the observations that depends not only on the total choices and stable models of a PASP but also on a certain function $d$ that must respect some conditions. To simplify the notation we use the subscript in $w_d$ only when necessary. | |
| 352 | + \item The last point defines a ``weight'' function on the inputs that depends not only on the total choices and stable models of a PASP but also on a certain function $d$ that must respect some conditions. To simplify the notation we use the subscript in $w_d$ only when necessary. | |
| 298 | 353 | % |
| 299 | - \item At first, it may seem counter-intuitive that $w\at{\emptyset} = \sum_{s\in\fml{S}} w\at{s}$ is the largest ``weight'' in the lattice. But $\emptyset$, as an interpretation, sets zero restrictions on the ``compatible'' stable models. The ``complement'' of $\bot = \emptyset$ is the \emph{maximal inconsistent} observation $\top = \fml{A} \cup \cset{\neg a }{ a \in \fml{A}}$. | |
| 354 | + \item At first, it may seem counter-intuitive that $w\at{\emptyset} = \sum_{s\in\fml{S}} w\at{s}$ is the largest ``weight'' in the lattice. But $\emptyset$, as an interpretation, sets zero restrictions on the ``compatible'' stable models. The ``complement'' of $\bot = \emptyset$ is the \emph{maximal inconsistent} input $\top = \fml{A} \cup \cset{\neg a }{ a \in \fml{A}}$. | |
| 300 | 355 | % |
| 301 | 356 | \item \textbf{We haven't yet defined a probability measure.} To do so we must define a set of samples $\Omega$, a set of events $F\subseteq \pset{\Omega}$ and a function $P:F\to\intcc{0,1}$ such that: |
| 302 | 357 | \begin{enumerate} | ... | ... |
text/00_PASP.toc
| 1 | 1 | \beamer@sectionintoc {1}{Introduction}{2}{0}{1} |
| 2 | -\beamer@sectionintoc {2}{Motivation}{8}{0}{2} | |
| 3 | -\beamer@sectionintoc {3}{Resolution}{10}{0}{3} | |
| 4 | -\beamer@sectionintoc {4}{Cases \& Examples}{14}{0}{4} | |
| 5 | -\beamer@subsectionintoc {4}{1}{Programs with disjunctive heads}{15}{0}{4} | |
| 6 | -\beamer@subsectionintoc {4}{2}{Non-stratified programs}{20}{0}{4} | |
| 7 | -\beamer@sectionintoc {5}{Conclusions}{25}{0}{5} | |
| 2 | +\beamer@sectionintoc {2}{Motivation}{10}{0}{2} | |
| 3 | +\beamer@sectionintoc {3}{Resolution}{12}{0}{3} | |
| 4 | +\beamer@sectionintoc {4}{Cases \& Examples}{17}{0}{4} | |
| 5 | +\beamer@subsectionintoc {4}{1}{Programs with disjunctive heads}{18}{0}{4} | |
| 6 | +\beamer@subsectionintoc {4}{2}{Non-stratified programs}{23}{0}{4} | |
| 7 | +\beamer@sectionintoc {5}{Conclusions}{28}{0}{5} | ... | ... |
text/00_PASP.xdv
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