Commit 237d62bda61e206c29f2a7e73a9a81960869bef8
1 parent
241956f9
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master
Further rewriting of 00_PASP
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363 additions
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352 deletions
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text/00_PASP.aux
... | ... | @@ -51,119 +51,115 @@ |
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text/00_PASP.fdb_latexmk
1 | 1 | # Fdb version 3 |
2 | -["xdvipdfmx"] 1667935664 "00_PASP.xdv" "00_PASP.pdf" "00_PASP" 1667935664 | |
3 | - "00_PASP.xdv" 1667935663 214680 71a3fe8c0e42560f8631e0d09f4181a7 "xelatex" | |
2 | +["xdvipdfmx"] 1668012215 "00_PASP.xdv" "00_PASP.pdf" "00_PASP" 1668012216 | |
3 | + "00_PASP.xdv" 1668012215 203892 0858b8d4b4e7e8aa8085e0bea6b8815a "xelatex" | |
4 | 4 | (generated) |
5 | 5 | "00_PASP.pdf" |
6 | -["xelatex"] 1667935657 "/home/fc/sci/projetos/zugzwang/text/00_PASP.tex" "00_PASP.xdv" "00_PASP" 1667935664 | |
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6 | +["xelatex"] 1668012209 "/home/fc/sci/projetos/zugzwang/text/00_PASP.tex" "00_PASP.xdv" "00_PASP" 1668012216 | |
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text/00_PASP.fls
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text/00_PASP.log
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694 | +LaTeX Info: Redefining \pageref on input line 77. | |
695 | +LaTeX Info: Redefining \nameref on input line 77. | |
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742 | 742 | (/usr/share/texmf-dist/tex/latex/translator/translator-basic-dictionary-English.dict |
743 | 743 | Dictionary: translator-basic-dictionary, Language: English |
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text/00_PASP.nav
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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}{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} | |
3 | +\beamer@slide {prop:lucases}{13} | |
4 | +\beamer@slide {prop:lucases.a}{13} | |
5 | +\beamer@slide {prop:lucases.b}{13} | |
6 | +\beamer@slide {prop:lucases.c}{13} | |
7 | +\beamer@slide {prop:lucases.d}{13} | |
8 | 8 | \beamer@slide {def:w.inconsistent}{16} |
9 | 9 | \beamer@slide {eq:prob.sm}{16} |
10 | 10 | \beamer@slide {def:w.disj}{16} |
11 | 11 | \beamer@slide {def:w.conj}{16} |
12 | 12 | \beamer@slide {def:w.empty}{16} |
13 | -\beamer@slide {eq:def.prob}{16} | |
14 | -\beamer@slide {eq:def.prob.event}{16} | |
13 | +\beamer@slide {eq:def.prob}{17} | |
14 | +\beamer@slide {eq:def.prob.event}{17} | ... | ... |
text/00_PASP.synctex.gz
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text/00_PASP.tex
... | ... | @@ -23,6 +23,18 @@ |
23 | 23 | \usepackage[overridenote]{pdfpc} |
24 | 24 | |
25 | 25 | \usepackage{tikz} |
26 | +\tikzset{ | |
27 | +rrect/.style={ | |
28 | + rectangle, | |
29 | + rounded corners, | |
30 | + fill=gray!10, | |
31 | + % minimum width=1em, | |
32 | + % text width=2em, | |
33 | + % draw=blue!75, | |
34 | + % very thick, | |
35 | + align=center, | |
36 | + } | |
37 | +} | |
26 | 38 | |
27 | 39 | \usepackage{commath} |
28 | 40 | \usepackage{amssymb} |
... | ... | @@ -96,10 +108,10 @@ |
96 | 108 | \item \textbf{Atoms} $\fml{A}$, |
97 | 109 | $\overline{\fml{A}} = \cset{\neg a}{a \in \fml{A}}$, |
98 | 110 | % -------------------------------- |
99 | - \item \textbf{Inputs} $\fml{Z}$: | |
111 | + \item \textbf{Samples} $\fml{Z}$: | |
100 | 112 | $$\fml{Z} = \cset{z = \alpha \cup \beta }{ \alpha \subseteq \fml{A} \land \beta \subseteq \overline{\fml{A}} }$$ |
101 | 113 | % -------------------------------- |
102 | - \item \textbf{Interpretations} or \textit{consistent inputs} $\fml{I}$ : | |
114 | + \item \textbf{Interpretations} or \textit{consistent samples} $\fml{I}$ : | |
103 | 115 | $$\fml{I} = \cset{z \in \fml{Z} }{ \forall a \in \fml{A}~\envert{\set{a,\neg a} \cap z} \leq 1}.$$ |
104 | 116 | % -------------------------------- |
105 | 117 | \item \textit{PASP Problem} or \textbf{Specification:} $P = C \land F \land R$ where |
... | ... | @@ -112,7 +124,7 @@ |
112 | 124 | % -------------------------------- |
113 | 125 | \item $R = R_P$ \textit{rules}. |
114 | 126 | % -------------------------------- |
115 | - \item $\fml{A}_P, \fml{Z}_P$ and $\fml{I}_P$: \textit{atoms}, \textit{inputs} and \textit{interpretations} of $P$. | |
127 | + \item $\fml{A}_P, \fml{Z}_P$ and $\fml{I}_P$: \textit{atoms}, \textit{samples} and \textit{interpretations} of $P$. | |
116 | 128 | \end{itemize} |
117 | 129 | % -------------------------------- |
118 | 130 | \item \textbf{Stable Models} of $P$, $\fml{S} = \fml{S}_P$, are the stable models of $\delta P = \delta C + F + R$. |
... | ... | @@ -142,9 +154,11 @@ |
142 | 154 | This is the \emph{distribution semantic} as set by Sato. |
143 | 155 | \end{frame} |
144 | 156 | % ================================================================ |
145 | -\begin{frame}{Problem Statement} | |
146 | - % -------------------------------- | |
147 | - How to \textit{extend} probability from total choices to stable models, interpretations and inputs? | |
157 | +\begin{frame} | |
158 | + % -------------------------------- | |
159 | + \begin{block}{Problem Statement} | |
160 | + How to \textit{extend} probability from total choices to stable models, interpretations and samples? | |
161 | + \end{block} | |
148 | 162 | % -------------------------------- |
149 | 163 | \begin{quotation} |
150 | 164 | There's a problem right at extending to stable models. |
... | ... | @@ -179,7 +193,7 @@ |
179 | 193 | % -------------------------------- |
180 | 194 | \item $\pr{\set{\neg a}} = 0.7$ is straightforward. |
181 | 195 | % -------------------------------- |
182 | - \item But, no \textit{unbiased} choice for $\alpha\in\intcc{0,1}$ in | |
196 | + \item But, no \textit{informed} choice for $\alpha\in\intcc{0,1}$ in | |
183 | 197 | $$ |
184 | 198 | \begin{aligned} |
185 | 199 | \pr{\set{a, b}} &= 0.3 \alpha, \cr |
... | ... | @@ -202,17 +216,17 @@ |
202 | 216 | \pr{\set{a, c}} &= 0.3 \co{\alpha}. |
203 | 217 | \end{aligned} |
204 | 218 | $$ |
205 | - \item A \textit{random variable} captures this: | |
219 | + \item A \textit{random variable} captures this uncertainty: | |
206 | 220 | $$ |
207 | 221 | \begin{aligned} |
208 | - \pr{\set{\neg a} \given\ A = \alpha } &= 0.7, \cr | |
209 | - \pr{\set{a, b} \given\ A = \alpha } &= 0.3 \alpha, \cr | |
210 | - \pr{\set{a, c} \given\ A = \alpha } &= 0.3 \co{\alpha}. | |
222 | + \pr{\set{\neg a} \given A = \alpha } &= 0.7, \cr | |
223 | + \pr{\set{a, b} \given A = \alpha } &= 0.3 \alpha, \cr | |
224 | + \pr{\set{a, c} \given A = \alpha } &= 0.3 \co{\alpha}. | |
211 | 225 | \end{aligned} |
212 | 226 | $$ |
213 | 227 | \item Other uncertainties lead to further parameters: |
214 | 228 | $$ |
215 | - \pr{s \given\ A_1 = \alpha_1, \ldots, A_n = \alpha_n }. | |
229 | + \pr{s \given A_1 = \alpha_1, \ldots, A_n = \alpha_n }. | |
216 | 230 | $$ |
217 | 231 | % -------------------------------- |
218 | 232 | \end{itemize} |
... | ... | @@ -220,14 +234,14 @@ |
220 | 234 | % -------------------------------- |
221 | 235 | \end{frame} |
222 | 236 | % ================================================================ |
223 | -\begin{frame}{Main Research Question} | |
237 | +\begin{frame}%{Main Research Question} | |
224 | 238 | % -------------------------------- |
225 | - A \textit{random variable} captures this: | |
239 | + A \textit{random variable} captures this uncertainty: | |
226 | 240 | $$ |
227 | 241 | \begin{aligned} |
228 | - \pr{\set{\neg a} \given\ A = \alpha } &= 0.7, \cr | |
229 | - \pr{\set{a, b} \given\ A = \alpha } &= 0.3 \alpha, \cr | |
230 | - \pr{\set{a, c} \given\ A = \alpha } &= 0.3 \co{\alpha}. | |
242 | + \pr{\set{\neg a} \given A = \alpha } &= 0.7, \cr | |
243 | + \pr{\set{a, b} \given A = \alpha } &= 0.3 \alpha, \cr | |
244 | + \pr{\set{a, c} \given A = \alpha } &= 0.3 \co{\alpha}. | |
231 | 245 | \end{aligned} |
232 | 246 | $$ |
233 | 247 | % -------------------------------- |
... | ... | @@ -237,49 +251,51 @@ |
237 | 251 | % -------------------------------- |
238 | 252 | \begin{itemize} |
239 | 253 | % -------------------------------- |
240 | - \item Follow ASP syntax; for each case, consider the possible uncertainty scenarios. | |
254 | + \item Follow ASP syntax; for each case, what are the uncertainty scenarios? | |
255 | + % -------------------------------- | |
256 | + \item The disjunction example illustrates one such scenario. | |
241 | 257 | % -------------------------------- |
242 | - \item The disjunction example illustrates one such step. | |
258 | + \item \textit{Neat} means a function $d: \fml{S} \to \intcc{0, 1}$ such that | |
259 | + $$ | |
260 | + \sum_{s\in\fml{S}_\theta} d\at{s} = 1 | |
261 | + $$ | |
262 | + for each $\theta \in \Theta$. | |
243 | 263 | % -------------------------------- |
244 | 264 | \end{itemize} |
245 | 265 | % -------------------------------- |
246 | 266 | \end{frame} |
247 | 267 | % ================================================================ |
248 | -\section{Motivation} | |
249 | -% ================================================================ | |
250 | -\begin{frame}{Specification, Data \& Evaluation} | |
268 | +\begin{frame}%{Specification, Data \& Evaluation} | |
251 | 269 | % -------------------------------- |
252 | - Given some procedure to extend probabilities to stable models, interpretations and inputs, and given: | |
270 | + Given a method that produces a distribution of samples, $p$, from a specification, $P$ and: | |
253 | 271 | % -------------------------------- |
254 | 272 | \begin{itemize} |
255 | 273 | % -------------------------------- |
256 | - \item $P$, a specification. | |
257 | - % -------------------------------- | |
258 | - \item $p$, the distribution of inputs from above. | |
259 | - % -------------------------------- | |
260 | - \item $Z$, a dataset of inputs. | |
274 | + \item $Z$, a dataset of samples. | |
261 | 275 | % -------------------------------- |
262 | 276 | \item $e$, the respective empirical distribution. |
263 | 277 | % -------------------------------- |
264 | 278 | \item $D$, some probability divergence, \textit{e.g.} Kullback-Leibler. |
265 | 279 | % -------------------------------- |
266 | 280 | \end{itemize} |
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} | |
281 | + % -------------------------------- | |
282 | + \begin{block}{Motivation} | |
283 | + Then $D\at{P} = D\at{e, p}$ 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}. | |
284 | + \end{block} | |
271 | 285 | % -------------------------------- |
272 | 286 | \end{frame} |
273 | 287 | % ================================================================ |
274 | -\section{Resolution} | |
288 | +\section{Extending Probability to Samples} | |
275 | 289 | % ================================================================ |
276 | 290 | \begin{frame}{Resolution Path} |
291 | + Prior to \textit{conciliation} with data: | |
277 | 292 | \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 $z \in \fml{Z} \setminus \fml{I}$. | |
293 | + \item Use \textit{conditional parameters} to represent lack of knowledge \emph{e.g.} $\alpha$ in the disjunction example. | |
294 | + \item This extends probability from total choices to \textit{standard models} --- \alert{hopefully}. | |
295 | + \item Assume probability set on standard models; Extend it to \textit{interpretations}. \textbf{How?} Later. | |
296 | + \item Set $\pr{z} = 0$ for $z \in \fml{Z} \setminus \fml{I}$ (inconsistent samples). | |
282 | 297 | \end{enumerate} |
298 | + Assuming a conditional probability set on stable models, \textit{How to extend it to interpretations?} | |
283 | 299 | \end{frame} |
284 | 300 | \begin{frame}{Bounds of Interpretations} |
285 | 301 | % -------------------------------- |
... | ... | @@ -295,7 +311,7 @@ |
295 | 311 | % -------------------------------- |
296 | 312 | \end{itemize} |
297 | 313 | % -------------------------------- |
298 | - \item\label{prop:lucases} \textbf{Proposition.} Stable models are \textit{minimal} so \textit{one} of the following cases takes place: | |
314 | + \item\label{prop:lucases} \textbf{Proposition.} Exactly \textit{one} of the following cases takes place: | |
299 | 315 | % -------------------------------- |
300 | 316 | \begin{enumerate} |
301 | 317 | % -------------------------------- |
... | ... | @@ -308,50 +324,125 @@ |
308 | 324 | \item\label{prop:lucases.d} $\lset{x} = \emptyset = \uset{x}$. |
309 | 325 | % -------------------------------- |
310 | 326 | \end{enumerate} |
327 | + because stable models are \textit{minimal}. | |
311 | 328 | % -------------------------------- |
312 | 329 | \end{itemize} |
313 | 330 | % -------------------------------- |
314 | 331 | \end{frame} |
315 | 332 | % ================================================================ |
333 | +\begin{frame}{Disjunction Example | The Interpretation's Lattice} | |
334 | + \begin{center} | |
335 | + \begin{tikzpicture} | |
336 | + % | |
337 | + \draw [help lines, color=gray!20] grid (11,7); | |
338 | + % | |
339 | + \node [fill=gray!50] (sm) at (1, 7) {sm}; | |
340 | + \node [draw,rrect] (sub) at (2, 7) {sub}; | |
341 | + \node [draw, fill=gray!10] (sup) at (3, 7) {sup}; | |
342 | + \node (ind) at (4, 7) {ind}; | |
343 | + % | |
344 | + \node [draw, rrect] (E) at (5.5,0) {$\emptyset$}; | |
345 | + % | |
346 | + \node [draw, rrect] (a) at (1.5,1.5) {$a$}; | |
347 | + \node [draw, rrect] (b) at (0,1.5) {$b$}; | |
348 | + \node [draw, rrect] (c) at (4.5,1.5) {$c$}; | |
349 | + \node [fill=gray!50] (A) at (8.5,1.5) {$\co{a}$}; | |
350 | + \node (B) at (9.5,1.5) {$\co{b}$}; | |
351 | + \node (C) at (10.5,1.5) {$\co{c}$}; | |
352 | + % | |
353 | + \node [fill=gray!50] (ab) at (0,4) {$ab$}; | |
354 | + \node [fill=gray!50] (ac) at (3,4) {$ac$}; | |
355 | + \node (aB) at (1,4) {$a\co{b}$}; | |
356 | + \node (aC) at (2,4) {$a\co{c}$}; | |
357 | + \node [draw, fill=gray!10] (Ab) at (4,4) {$\co{a}b$}; | |
358 | + \node [draw, fill=gray!10] (Ac) at (5,4) {$\co{a}c$}; | |
359 | + \node [draw, fill=gray!10] (AB) at (6,4) {$\co{a}\co{b}$}; | |
360 | + \node [draw, fill=gray!10] (AC) at (7,4) {$\co{a}\co{c}$}; | |
361 | + \node [fill=white] (bc) at (10,4) {$bc$}; | |
362 | + \node [fill=white] (bC) at (11,4) {$b\co{c}$}; | |
363 | + \node [fill=white] (Bc) at (12,4) {$\co{b}c$}; | |
364 | + \node [fill=white] (BC) at (13,4) {$\co{b}\co{c}$}; | |
365 | + % | |
366 | + \node [draw, fill=gray!10] (abc) at (1.5,6) {$abc$}; | |
367 | + \node (abC) at (3,6) {$ab\co{c}$}; | |
368 | + \node (aBc) at (4,6) {$a\co{b}c$}; | |
369 | + \node (aBC) at (5,6) {$a\co{b}\co{c}$}; | |
370 | + \node [draw, fill=gray!10] (Abc) at (7,6) {$\co{a}bc$}; | |
371 | + \node [draw, fill=gray!10] (AbC) at (8,6) {$\co{a}b\co{c}$}; | |
372 | + \node [draw, fill=gray!10] (ABc) at (9,6) {$\co{a}\co{b}c$}; | |
373 | + \node [draw, fill=gray!10] (ABC) at (10,6) {$\co{a}\co{b}\co{c}$}; | |
374 | + % | |
375 | + \draw [->] (ab) to [out=270,in=180] (E); | |
376 | + \draw [->] (ab) to [out=270,in=90] (a); | |
377 | + \draw [->] (ab) to [out=270,in=90] (b); | |
378 | + \draw [->] (ab) to [out=90,in=270] (abc); | |
379 | + % | |
380 | + \draw [->] (ac) to [out=270,in=180] (E); | |
381 | + \draw [->] (ac) to [out=270,in=90] (a); | |
382 | + \draw [->] (ac) to [out=270,in=90] (c); | |
383 | + \draw [->] (ac) to [out=90,in=270] (abc); | |
384 | + % | |
385 | + \draw [->] (A) to [out=270,in=0] (E); | |
386 | + % | |
387 | + \draw [->] (A) to [out=90,in=270] (Abc); | |
388 | + \draw [->] (A) to [out=90,in=270] (AbC); | |
389 | + \draw [->] (A) to [out=90,in=270] (ABc); | |
390 | + \draw [->] (A) to [out=90,in=270] (ABC); | |
391 | + % | |
392 | + \draw [->] (A) to [out=90,in=270] (Ab); | |
393 | + \draw [->] (A) to [out=90,in=270] (Ac); | |
394 | + \draw [->] (A) to [out=90,in=270] (AB); | |
395 | + \draw [->] (A) to [out=90,in=270] (AC); | |
396 | + \end{tikzpicture} | |
397 | + \end{center} | |
398 | +\end{frame} | |
399 | +% ================================================================ | |
316 | 400 | \begin{frame} |
317 | 401 | |
318 | - Next we try to formalize the possible configurations of this scenario. Consider the ASP program $P = C \land F \land R$ with total choices $\Theta $ and stable models $\fml{S}$. Let $d :: \fml{S} \to \intcc{0,1}$ such that $\sum_{s\in\fml{S}_\theta} d\at{s} = 1$. | |
402 | + | |
403 | + \begin{itemize} | |
404 | + \item Consider the ASP program $P = C \land F \land R$ with total choices $\Theta $ and stable models $\fml{S}$. | |
405 | + | |
406 | + \item Let $d : \fml{S} \to \intcc{0,1}$ such that $\sum_{s\in\fml{S}_\theta} d\at{s} = 1$ for each $\theta \in \Theta$. | |
407 | + \end{itemize} | |
319 | 408 | \end{frame} |
320 | 409 | % ================================================================ |
321 | 410 | \begin{frame} |
322 | - | |
411 | + For each $z\in\fml{Z}$ only one of the following cases takes place | |
323 | 412 | \begin{enumerate} |
324 | - \item For each $z\in\fml{Z}$ only one of the following cases takes place | |
413 | + \item $z$ is inconsistent. Then \textbf{define} | |
414 | + \begin{equation} | |
415 | + w_d\at{x} = 0.\label{def:w.inconsistent} | |
416 | + \end{equation} | |
417 | + % | |
418 | + \item $z$ is an interpretation and $\lset{z} = \set{z} = \uset{z}$. Then $z$ is a stable model and \textbf{define} | |
419 | + \begin{equation} | |
420 | + w_d\at{z} = w\at{z} = d\at{z} \pr{\theta_z}.\label{eq:prob.sm} | |
421 | + \end{equation} | |
422 | + % | |
423 | + \item $z$ is an interpretation and $\lset{z} \neq \emptyset \land \uset{x} = \emptyset$. Then \textbf{define} | |
424 | + \begin{equation} | |
425 | + w_d\at{z} = \sum_{s \in \lset{z}} w_d\at{s}.\label{def:w.disj} | |
426 | + \end{equation} | |
427 | + % | |
428 | + \item $z$ is an interpretation and $\lset{z} = \emptyset \land \uset{z} \neq \emptyset$. Then \textbf{define} | |
429 | + \begin{equation} | |
430 | + w_d\at{z} = \prod_{s \in \uset{z}} w_d\at{s}.\label{def:w.conj} | |
431 | + \end{equation} | |
432 | + % | |
433 | + \item $z$ is an interpretation and $\lset{z} = \emptyset \land \uset{z} = \emptyset$. Then \textbf{define} | |
434 | + \begin{equation} | |
435 | + w_d\at{z} = 0.\label{def:w.empty} | |
436 | + \end{equation} | |
437 | + \end{enumerate} | |
438 | + \end{frame} | |
439 | + % ================================================================ | |
440 | + \begin{frame} | |
325 | 441 | \begin{enumerate} |
326 | - \item $z$ is inconsistent. Then \textbf{define} | |
327 | - \begin{equation} | |
328 | - w_d\at{x} = 0.\label{def:w.inconsistent} | |
329 | - \end{equation} | |
330 | - % | |
331 | - \item $z$ is an interpretation and $\lset{z} = \set{z} = \uset{x}$. Then $z = s$ is a stable model and \textbf{define} | |
332 | - \begin{equation} | |
333 | - w_d\at{z} = w\at{s} = d\at{s} \pr{\theta_s}.\label{eq:prob.sm} | |
334 | - \end{equation} | |
335 | - % | |
336 | - \item $z$ is an interpretation and $\lset{z} \neq \emptyset \land \uset{x} = \emptyset$. Then \textbf{define} | |
337 | - \begin{equation} | |
338 | - w_d\at{z} = \sum_{s \in \lset{z}} w_d\at{s}.\label{def:w.disj} | |
339 | - \end{equation} | |
340 | - % | |
341 | - \item $z$ is an interpretation and $\lset{z} = \emptyset \land \uset{z} \neq \emptyset$. Then \textbf{define} | |
342 | - \begin{equation} | |
343 | - w_d\at{z} = \prod_{s \in \uset{z}} w_d\at{s}.\label{def:w.conj} | |
344 | - \end{equation} | |
345 | - % | |
346 | - \item $z$ is an interpretation and $\lset{z} = \emptyset \land \uset{z} = \emptyset$. Then \textbf{define} | |
347 | - \begin{equation} | |
348 | - w_d\at{z} = 0.\label{def:w.empty} | |
349 | - \end{equation} | |
350 | - \end{enumerate} | |
351 | 442 | % |
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. | |
443 | + \item The last point defines a ``weight'' function on the samples 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. | |
353 | 444 | % |
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 $\top = \fml{A} \cup \cset{\neg a }{ a \in \fml{A}}$. | |
445 | + \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} sample $\top = \fml{A} \cup \cset{\neg a }{ a \in \fml{A}}$. | |
355 | 446 | % |
356 | 447 | \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: |
357 | 448 | \begin{enumerate} |
... | ... | @@ -432,69 +523,6 @@ |
432 | 523 | % ================================================================ |
433 | 524 | \begin{frame} |
434 | 525 | |
435 | - Now consider all the interpretations for this program: | |
436 | - \begin{center} | |
437 | - \begin{tikzpicture} | |
438 | - %\draw [help lines] grid (11,3); | |
439 | - % | |
440 | - \node [draw, circle] (E) at (5.5,0) {$\emptyset$}; | |
441 | - % | |
442 | - \node [draw, circle] (a) at (3,2) {$a$}; | |
443 | - \node [draw, circle] (b) at (2,2) {$b$}; | |
444 | - \node [draw, circle] (c) at (4,2) {$c$}; | |
445 | - \node [fill=gray!50] (A) at (8,2) {$\co{a}$}; | |
446 | - \node (B) at (9,2) {$\co{b}$}; | |
447 | - \node (C) at (7,2) {$\co{c}$}; | |
448 | - % | |
449 | - \node [fill=gray!50] (ab) at (0,4) {$ab$}; | |
450 | - \node [fill=gray!50] (ac) at (1,4) {$ac$}; | |
451 | - \node (aB) at (2,4) {$a\co{b}$}; | |
452 | - \node (aC) at (3,4) {$a\co{c}$}; | |
453 | - \node [draw] (Ab) at (4,4) {$\co{a}b$}; | |
454 | - \node [draw] (Ac) at (5,4) {$\co{a}c$}; | |
455 | - \node [draw] (AB) at (6,4) {$\co{a}\co{b}$}; | |
456 | - \node [draw] (AC) at (7,4) {$\co{a}\co{c}$}; | |
457 | - \node [fill=white] (bc) at (10,4) {$bc$}; | |
458 | - \node [fill=white] (bC) at (11,4) {$b\co{c}$}; | |
459 | - \node [fill=white] (Bc) at (12,4) {$\co{b}c$}; | |
460 | - \node [fill=white] (BC) at (13,4) {$\co{b}\co{c}$}; | |
461 | - % | |
462 | - \node [draw] (abc) at (0.5,6) {$abc$}; | |
463 | - \node (abC) at (3,6) {$ab\co{c}$}; | |
464 | - \node (aBc) at (4,6) {$a\co{b}c$}; | |
465 | - \node (aBC) at (5,6) {$a\co{b}\co{c}$}; | |
466 | - \node [draw] (Abc) at (7,6) {$\co{a}bc$}; | |
467 | - \node [draw] (AbC) at (8,6) {$\co{a}b\co{c}$}; | |
468 | - \node [draw] (ABc) at (9,6) {$\co{a}\co{b}c$}; | |
469 | - \node [draw] (ABC) at (10,6) {$\co{a}\co{b}\co{c}$}; | |
470 | - % | |
471 | - \draw [->] (ab) to [out=270,in=180] (E); | |
472 | - \draw [->] (ab) to [out=270,in=90] (a); | |
473 | - \draw [->] (ab) to [out=270,in=90] (b); | |
474 | - \draw [->] (ab) to [out=90,in=270] (abc); | |
475 | - % | |
476 | - \draw [->] (ac) to [out=270,in=180] (E); | |
477 | - \draw [->] (ac) to [out=270,in=90] (a); | |
478 | - \draw [->] (ac) to [out=270,in=90] (c); | |
479 | - \draw [->] (ac) to [out=90,in=270] (abc); | |
480 | - % | |
481 | - \draw [->] (A) to [out=270,in=0] (E); | |
482 | - % | |
483 | - \draw [->] (A) to [out=90,in=270] (Abc); | |
484 | - \draw [->] (A) to [out=90,in=270] (AbC); | |
485 | - \draw [->] (A) to [out=90,in=270] (ABc); | |
486 | - \draw [->] (A) to [out=90,in=270] (ABC); | |
487 | - % | |
488 | - \draw [->] (A) to [out=90,in=270] (Ab); | |
489 | - \draw [->] (A) to [out=90,in=270] (Ac); | |
490 | - \draw [->] (A) to [out=90,in=270] (AB); | |
491 | - \draw [->] (A) to [out=90,in=270] (AC); | |
492 | - \end{tikzpicture} | |
493 | - \end{center} | |
494 | -\end{frame} | |
495 | -% ================================================================ | |
496 | -\begin{frame} | |
497 | - | |
498 | 526 | In this diagram: |
499 | 527 | \begin{itemize} |
500 | 528 | \item Negations are represented as \emph{e.g.} $\co{a}$ instead of $\neg a$; Stable models are denoted by shaded nodes as \tikz{\node[fill=gray!50] {$ab$}}. | ... | ... |
text/00_PASP.toc
1 | 1 | \beamer@sectionintoc {1}{Introduction}{2}{0}{1} |
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} | |
2 | +\beamer@sectionintoc {2}{Extending Probability to Samples}{11}{0}{2} | |
3 | +\beamer@sectionintoc {3}{Cases \& Examples}{18}{0}{3} | |
4 | +\beamer@subsectionintoc {3}{1}{Programs with disjunctive heads}{19}{0}{3} | |
5 | +\beamer@subsectionintoc {3}{2}{Non-stratified programs}{23}{0}{3} | |
6 | +\beamer@sectionintoc {4}{Conclusions}{28}{0}{4} | ... | ... |
text/00_PASP.xdv
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