rlm@10
|
1 #+title: Discovering Effective Pok\eacute{}mon Types Using Linear Optimization
|
rlm@0
|
2 #+author: Robert McIntyre & Dylan Holmes
|
rlm@0
|
3 #+EMAIL: rlm@mit.edu
|
rlm@12
|
4 #+description: Using Lpsolve to find effective pokemon types in clojure.
|
rlm@12
|
5 #+keywords: Pokemon, clojure, linear optimization, lp_solve, LpSolve
|
rlm@4
|
6 #+SETUPFILE: ../../aurellem/org/setup.org
|
rlm@2
|
7 #+INCLUDE: ../../aurellem/org/level-0.org
|
rlm@4
|
8
|
rlm@0
|
9 * Introduction
|
rlm@11
|
10 This post continues the [[./types.org][previous one]] about pok\eacute{}mon types.
|
rlm@11
|
11 Pok\eacute{}mon is a game in which adorable creatures battle each
|
rlm@11
|
12 other using fantastic attacks. It was made into a several gameboy
|
rlm@11
|
13 games that all share the same battle system. Every pok\eacute{}mon in
|
rlm@11
|
14 the gameboy game has one or two /types/, such as Ground, Fire, Water,
|
rlm@11
|
15 etc. Every pok\eacute{}mon attack has exactly one type. Certain
|
rlm@11
|
16 defending types are weak or strong to other attacking types. For
|
rlm@11
|
17 example, Water attacks are strong against Fire pok\eacute{}mon, while
|
rlm@11
|
18 Electric attacks are weak against Ground Pok\eacute{}mon. In the
|
rlm@11
|
19 games, attacks can be either twice as effective as normal (Water
|
rlm@11
|
20 vs. Fire), neutrally effective (Normal vs. Normal), half as effective
|
rlm@11
|
21 (Fire vs. Water), or not effective at all (Electric vs. Ground). We
|
rlm@12
|
22 represent these strengths and weaknesses as the numbers 2, 1,
|
rlm@11
|
23 $\frac{1}{2}$, and 0, and call them the /susceptance/ of one type to
|
rlm@11
|
24 another.
|
rlm@0
|
25
|
rlm@11
|
26 If a pokemon has two types, then the strengths and weakness of each
|
rlm@11
|
27 type are /multiplied/ together. Thus Electric (2x weak to Ground)
|
rlm@11
|
28 combined with Flying (immune to Ground (0x)) is immune to Ground.
|
rlm@11
|
29 Fire (2x weak to Water) combined with Water (1/2x resistant to Water)
|
rlm@11
|
30 is neutral to Water. If both types are resistant to another type, then
|
rlm@11
|
31 the combination is doubly-resistant (1/4x) to that type. If both types
|
rlm@11
|
32 are weak to a certain type then the combination is double-weak (4x) to
|
rlm@11
|
33 that type.
|
rlm@11
|
34
|
rlm@11
|
35 In the [[./types.org][previous post]], we used the best-first search algorithm to find
|
rlm@11
|
36 the most effective Pok\eacute{}mon type combinations. Afterwards, we
|
rlm@11
|
37 realized that we could transform this search problem into a /linear
|
rlm@12
|
38 optimization problem/. This conversion offers several advantages:
|
rlm@11
|
39 first, search algorithms are comparatively slow, whereas linear
|
rlm@11
|
40 optimization algorithms are extremely fast; second, it is difficult to
|
rlm@11
|
41 determine whether a search problem has any solution, whereas it is
|
rlm@11
|
42 straightforward to determine whether a linear optimization problem has
|
rlm@11
|
43 any solution; finally, because systems of linear equations are so
|
rlm@11
|
44 common, many programming languages have linear equation solvers
|
rlm@11
|
45 written for them.
|
rlm@11
|
46
|
rlm@11
|
47 In this article, we will:
|
rlm@0
|
48 - Solve a simple linear optimization problem in C :: We demonstrate
|
rlm@0
|
49 how to use the linear programming C library, =lp_solve=, to
|
rlm@11
|
50 solve a simple linear optimization problem.
|
rlm@0
|
51 - Incorporate a C library into Clojure :: We will show how we gave
|
rlm@0
|
52 Clojure access to the linear programming C library, =lp_solve=.
|
rlm@0
|
53 - Find effective Pokemon types using linear programming :: Building
|
rlm@11
|
54 on our earlier code, we answer some questions that were
|
rlm@11
|
55 impossible to answer using best-first search.
|
rlm@11
|
56 - Present our results :: We found some cool examples and learned a lot
|
rlm@11
|
57 about the pok\eacute{}mon type system as a whole.
|
rlm@0
|
58
|
rlm@0
|
59
|
rlm@0
|
60 ** Immortal Types
|
rlm@13
|
61
|
rlm@11
|
62 In the game, pok\eacute{}mon can have either one type or two types. If
|
rlm@11
|
63 this restriction is lifted, is there any combination of types that is
|
rlm@0
|
64 resistant to all types? I call such a combination an /Immortal Type/,
|
rlm@0
|
65 since if that type's pattern was repeated over and over again towards
|
rlm@0
|
66 infinity, the resulting type would be immune to all attack types.
|
rlm@0
|
67
|
rlm@0
|
68 * Linear Programming
|
rlm@0
|
69
|
rlm@0
|
70 Linear programming is the process of finding an optimal solution to a
|
rlm@0
|
71 linear equation of several variables which are constrained by some linear
|
rlm@0
|
72 inequalities.
|
rlm@0
|
73
|
rlm@0
|
74 ** The Farmer's Problem
|
rlm@0
|
75
|
rlm@10
|
76 Let's solve the Farmer's Problem, an example linear programming problem
|
rlm@0
|
77 borrowed from http://lpsolve.sourceforge.net/5.5/formulate.htm.
|
rlm@0
|
78
|
rlm@0
|
79
|
rlm@0
|
80 #+BEGIN_QUOTE
|
rlm@0
|
81 *The Farmer's Problem:* Suppose a farmer has 75 acres on which to
|
rlm@0
|
82 plant two crops: wheat and barley. To produce these crops, it costs
|
rlm@0
|
83 the farmer (for seed, fertilizer, etc.) $120 per acre for the wheat
|
rlm@0
|
84 and $210 per acre for the barley. The farmer has $15000 available for
|
rlm@0
|
85 expenses. But after the harvest, the farmer must store the crops while
|
rlm@0
|
86 awaiting favorable market conditions. The farmer has storage space
|
rlm@0
|
87 for 4000 bushels. Each acre yields an average of 110 bushels of wheat
|
rlm@0
|
88 or 30 bushels of barley. If the net profit per bushel of wheat (after
|
rlm@0
|
89 all expenses have been subtracted) is $1.30 and for barley is $2.00,
|
rlm@0
|
90 how should the farmer plant the 75 acres to maximize profit?
|
rlm@0
|
91 #+END_QUOTE
|
rlm@0
|
92
|
rlm@0
|
93 The Farmer's Problem is to maximize profit subject to constraints on
|
rlm@0
|
94 available farmland, funds for expenses, and storage space.
|
rlm@0
|
95
|
rlm@0
|
96 | | Wheat | Barley | Maximum total |
|
rlm@0
|
97 |----------+----------------------+---------------------+--------------|
|
rlm@0
|
98 | / | < | > | <> |
|
rlm@0
|
99 | Farmland | \(w\) acres | \(b\) acres | 75 acres |
|
rlm@0
|
100 | Expense | $120 per acre | $210 per acre | $15000 |
|
rlm@0
|
101 | Storage | 110 bushels per acre | 30 bushels per acre | 4000 bushels |
|
rlm@0
|
102 |----------+----------------------+---------------------+--------------|
|
rlm@0
|
103 | Profit | $1.30 per bushel | $2.00 per bushel | |
|
rlm@0
|
104
|
rlm@0
|
105 ** Solution using LP Solve
|
rlm@0
|
106 In a new file, =farmer.lp=, we list the variables and constraints
|
rlm@0
|
107 of our problem using LP Solve syntax.
|
rlm@0
|
108
|
rlm@3
|
109 #+begin_src lpsolve :tangle ../lp/farmer.lp
|
rlm@0
|
110 /* Maximize Total Profit */
|
rlm@0
|
111 max: +143 wheat +60 barley;
|
rlm@0
|
112
|
rlm@0
|
113
|
rlm@0
|
114 /* -------- Constraints --------*/
|
rlm@0
|
115
|
rlm@0
|
116 /* the farmer can't spend more money than he has */
|
rlm@0
|
117 +120 wheat +210 barley <= 15000;
|
rlm@0
|
118
|
rlm@0
|
119 /* the harvest has to fit in his storage space */
|
rlm@0
|
120 +110 wheat +30 barley <= 4000;
|
rlm@0
|
121
|
rlm@0
|
122 /* he can't use more acres than he owns */
|
rlm@0
|
123 +wheat +barley <= 75;
|
rlm@0
|
124 #+end_src
|
rlm@0
|
125
|
rlm@0
|
126 Running the =lp_solve= program on =farmer.lp= yields the following output.
|
rlm@0
|
127
|
rlm@0
|
128 #+begin_src sh :exports both :results scalar
|
rlm@11
|
129 lp_solve ~/proj/pokemon-types/lp/farmer.lp
|
rlm@0
|
130 #+end_src
|
rlm@0
|
131
|
rlm@0
|
132 #+results:
|
rlm@0
|
133 :
|
rlm@0
|
134 : Value of objective function: 6315.62500000
|
rlm@0
|
135 :
|
rlm@0
|
136 : Actual values of the variables:
|
rlm@0
|
137 : wheat 21.875
|
rlm@0
|
138 : barley 53.125
|
rlm@0
|
139
|
rlm@16
|
140
|
rlm@0
|
141 This shows that the farmer can maximize his profit by planting 21.875
|
rlm@0
|
142 of the available acres with wheat and the remaining 53.125 acres with
|
rlm@0
|
143 barley; by doing so, he will make $6315.62(5) in profit.
|
rlm@0
|
144
|
rlm@0
|
145 * Incorporating =lp_solve= into Clojure
|
rlm@0
|
146
|
rlm@11
|
147 There is a [[http://lpsolve.sourceforge.net/5.5/Java/README.html][Java API]] written by Juergen Ebert which enables Java
|
rlm@11
|
148 programs to use =lp_solve=. Although Clojure can use this Java API
|
rlm@11
|
149 directly, the interaction between Java, C, and Clojure is clumsy:
|
rlm@0
|
150
|
rlm@0
|
151 ** The Farmer's Problem in Clojure
|
rlm@11
|
152
|
rlm@0
|
153 We are going to solve the same problem involving wheat and barley,
|
rlm@11
|
154 that we did above, but this time using clojure and the =lp_solve= API.
|
rlm@0
|
155
|
rlm@16
|
156 #+name: intro
|
rlm@0
|
157 #+begin_src clojure :results silent
|
rlm@0
|
158 (ns pokemon.lpsolve
|
rlm@11
|
159 (:import lpsolve.LpSolve)
|
rlm@11
|
160 (:require pokemon.types)
|
rlm@16
|
161 (:require incanter.core)
|
rlm@13
|
162 (:require rlm.map-utils))
|
rlm@0
|
163 #+end_src
|
rlm@0
|
164
|
rlm@11
|
165 The =lp_solve= Java interface is available from the same site as
|
rlm@11
|
166 =lp_solve= itself, http://lpsolve.sourceforge.net/ Using it is the
|
rlm@11
|
167 same as many other =C= programs. There are excellent instructions to
|
rlm@11
|
168 get set up. The short version is that you must call Java with
|
rlm@0
|
169 =-Djava.library.path=/path/to/lpsolve/libraries= and also add the
|
rlm@0
|
170 libraries to your export =LD_LIBRARY_PATH= if you are using Linux. For
|
rlm@0
|
171 example, in my =.bashrc= file, I have the line
|
rlm@11
|
172 =LD_LIBRARY_PATH=$HOME/roBin/lpsolve:$LD_LIBRARY_PATH=. If everything
|
rlm@11
|
173 is set-up correctly,
|
rlm@0
|
174
|
rlm@16
|
175 #+name: body
|
rlm@0
|
176 #+begin_src clojure :results verbatim :exports both
|
rlm@0
|
177 (import 'lpsolve.LpSolve)
|
rlm@0
|
178 #+end_src
|
rlm@0
|
179
|
rlm@0
|
180 #+results: body
|
rlm@0
|
181 : lpsolve.LpSolve
|
rlm@0
|
182
|
rlm@0
|
183 should run with no problems.
|
rlm@0
|
184
|
rlm@0
|
185 ** Making a DSL to talk with LpSolve
|
rlm@0
|
186 *** Problems
|
rlm@0
|
187 Since we are using a =C= wrapper, we have to deal with manual memory
|
rlm@0
|
188 management for the =C= structures which are wrapped by the =LpSolve=
|
rlm@0
|
189 object. Memory leaks in =LpSolve= instances can crash the JVM, so it's
|
rlm@0
|
190 very important to get it right. Also, the Java wrapper follows the
|
rlm@0
|
191 =C= tradition closely and defines many =static final int= constants
|
rlm@0
|
192 for the different states of the =LpSolve= instance instead of using Java
|
rlm@0
|
193 enums. The calling convention for adding rows and columns to
|
rlm@0
|
194 the constraint matrix is rather complicated and must be done column by
|
rlm@0
|
195 column or row by row, which can be error prone. Finally, I'd like to
|
rlm@0
|
196 gather all the important output information from the =LpSolve= instance
|
rlm@0
|
197 into a final, immutable structure.
|
rlm@0
|
198
|
rlm@0
|
199 In summary, the issues I'd like to address are:
|
rlm@0
|
200
|
rlm@0
|
201 - reliable memory management
|
rlm@0
|
202 - functional interface to =LpSolve=
|
rlm@0
|
203 - intelligible, immutable output
|
rlm@0
|
204
|
rlm@0
|
205 To deal with these issues I'll create four functions for interfacing
|
rlm@0
|
206 with =LpSolve=
|
rlm@0
|
207
|
rlm@16
|
208 #+name: declares
|
rlm@0
|
209 #+begin_src clojure :results silent
|
rlm@0
|
210 (in-ns 'pokemon.lpsolve)
|
rlm@0
|
211
|
rlm@0
|
212 ;; deal with automatic memory management for LpSolve instance.
|
rlm@0
|
213 (declare linear-program)
|
rlm@0
|
214
|
rlm@0
|
215 ;; functional interface to LpSolve
|
rlm@0
|
216 (declare lp-solve)
|
rlm@0
|
217
|
rlm@0
|
218 ;; immutable output from lp-solve
|
rlm@0
|
219 (declare solve get-results)
|
rlm@0
|
220 #+end_src
|
rlm@0
|
221
|
rlm@11
|
222
|
rlm@0
|
223 *** Memory Management
|
rlm@0
|
224
|
rlm@0
|
225 Every instance of =LpSolve= must be manually garbage collected via a
|
rlm@0
|
226 call to =deleteLP=. I use a non-hygienic macro similar to =with-open=
|
rlm@0
|
227 to ensure that =deleteLP= is always called.
|
rlm@0
|
228
|
rlm@16
|
229 #+name: memory-management
|
rlm@0
|
230 #+begin_src clojure :results silent
|
rlm@0
|
231 (in-ns 'pokemon.lpsolve)
|
rlm@0
|
232 (defmacro linear-program
|
rlm@0
|
233 "solve a linear programming problem using LpSolve syntax.
|
rlm@0
|
234 within the macro, the variable =lps= is bound to the LpSolve instance."
|
rlm@0
|
235 [& statements]
|
rlm@0
|
236 (list 'let '[lps (LpSolve/makeLp 0 0)]
|
rlm@0
|
237 (concat '(try)
|
rlm@0
|
238 statements
|
rlm@0
|
239 ;; always free the =C= data structures.
|
rlm@0
|
240 '((finally (.deleteLp lps))))))
|
rlm@0
|
241 #+end_src
|
rlm@0
|
242
|
rlm@0
|
243
|
rlm@0
|
244 The macro captures the variable =lps= within its body, providing for a
|
rlm@0
|
245 convenient way to access the object using any of the methods of the
|
rlm@0
|
246 =LpSolve= API without having to worry about when to call
|
rlm@0
|
247 =deleteLP=.
|
rlm@0
|
248
|
rlm@0
|
249 *** Sensible Results
|
rlm@0
|
250 The =linear-program= macro deletes the actual =lps= object once it is
|
rlm@0
|
251 done working, so it's important to collect the important results and
|
rlm@0
|
252 add return them in an immutable structure at the end.
|
rlm@0
|
253
|
rlm@16
|
254 #+name: get-results
|
rlm@0
|
255 #+begin_src clojure :results silent
|
rlm@0
|
256 (in-ns 'pokemon.lpsolve)
|
rlm@0
|
257
|
rlm@0
|
258 (defrecord LpSolution
|
rlm@0
|
259 [objective-value
|
rlm@0
|
260 optimal-values
|
rlm@0
|
261 variable-names
|
rlm@0
|
262 solution
|
rlm@0
|
263 status
|
rlm@0
|
264 model])
|
rlm@0
|
265
|
rlm@0
|
266 (defn model
|
rlm@0
|
267 "Returns a textual representation of the problem suitable for
|
rlm@0
|
268 direct input to the =lp_solve= program (lps format)"
|
rlm@0
|
269 [#^LpSolve lps]
|
rlm@0
|
270 (let [target (java.io.File/createTempFile "lps" ".lp")]
|
rlm@0
|
271 (.writeLp lps (.getPath target))
|
rlm@0
|
272 (slurp target)))
|
rlm@0
|
273
|
rlm@0
|
274 (defn results
|
rlm@11
|
275 "Given an LpSolve object, solves the object and returns a map of the
|
rlm@0
|
276 essential values which compose the solution."
|
rlm@0
|
277 [#^LpSolve lps]
|
rlm@0
|
278 (locking lps
|
rlm@0
|
279 (let [status (solve lps)
|
rlm@0
|
280 number-of-variables (.getNcolumns lps)
|
rlm@0
|
281 optimal-values (double-array number-of-variables)
|
rlm@0
|
282 optimal-values (do (.getVariables lps optimal-values)
|
rlm@0
|
283 (seq optimal-values))
|
rlm@0
|
284 variable-names
|
rlm@11
|
285 (doall
|
rlm@11
|
286 ;; The doall is necessary since the lps object might
|
rlm@11
|
287 ;; soon be deleted.
|
rlm@0
|
288 (map
|
rlm@0
|
289 #(.getColName lps (inc %))
|
rlm@0
|
290 (range number-of-variables)))
|
rlm@0
|
291 model (model lps)]
|
rlm@0
|
292 (LpSolution.
|
rlm@0
|
293 (.getObjective lps)
|
rlm@0
|
294 optimal-values
|
rlm@0
|
295 variable-names
|
rlm@0
|
296 (zipmap variable-names optimal-values)
|
rlm@0
|
297 status
|
rlm@0
|
298 model))))
|
rlm@0
|
299
|
rlm@0
|
300 #+end_src
|
rlm@0
|
301
|
rlm@0
|
302 Here I've created an object called =LpSolution= which stores the
|
rlm@0
|
303 important results from a session with =lp_solve=. Of note is the
|
rlm@0
|
304 =model= function which returns the problem in a form that can be
|
rlm@0
|
305 solved by other linear programming packages.
|
rlm@0
|
306
|
rlm@0
|
307 *** Solution Status of an LpSolve Object
|
rlm@0
|
308
|
rlm@16
|
309 #+name: solve
|
rlm@0
|
310 #+begin_src clojure :results silent
|
rlm@0
|
311 (in-ns 'pokemon.lpsolve)
|
rlm@0
|
312
|
rlm@0
|
313 (defn static-integer?
|
rlm@0
|
314 "does the field represent a static integer constant?"
|
rlm@0
|
315 [#^java.lang.reflect.Field field]
|
rlm@0
|
316 (and (java.lang.reflect.Modifier/isStatic (.getModifiers field))
|
rlm@0
|
317 (integer? (.get field nil))))
|
rlm@0
|
318
|
rlm@0
|
319 (defn integer-constants [class]
|
rlm@0
|
320 (filter static-integer? (.getFields class)))
|
rlm@0
|
321
|
rlm@16
|
322 (defn constant-map
|
rlm@0
|
323 "Takes a class and creates a map of the static constant integer
|
rlm@0
|
324 fields with their names. This helps with C wrappers where they have
|
rlm@13
|
325 just defined a bunch of integer constants instead of enums."
|
rlm@0
|
326 [class]
|
rlm@0
|
327 (let [integer-fields (integer-constants class)]
|
rlm@0
|
328 (into (sorted-map)
|
rlm@0
|
329 (zipmap (map #(.get % nil) integer-fields)
|
rlm@0
|
330 (map #(.getName %) integer-fields)))))
|
rlm@16
|
331
|
rlm@16
|
332 (alter-var-root #'constant-map memoize)
|
rlm@0
|
333
|
rlm@0
|
334 (defn solve
|
rlm@0
|
335 "Solve an instance of LpSolve and return a string representing the
|
rlm@0
|
336 status of the computation. Will only solve a particular LpSolve
|
rlm@0
|
337 instance once."
|
rlm@0
|
338 [#^LpSolve lps]
|
rlm@0
|
339 ((constant-map LpSolve)
|
rlm@0
|
340 (.solve lps)))
|
rlm@0
|
341
|
rlm@0
|
342 #+end_src
|
rlm@0
|
343
|
rlm@0
|
344 The =.solve= method of an =LpSolve= object only returns an integer code
|
rlm@0
|
345 to specify the status of the computation. The =solve= method here
|
rlm@0
|
346 uses reflection to look up the actual name of the status code and
|
rlm@0
|
347 returns a more helpful status message that is also resistant to
|
rlm@0
|
348 changes in the meanings of the code numbers.
|
rlm@0
|
349
|
rlm@0
|
350 *** The Farmer Example in Clojure, Pass 1
|
rlm@0
|
351
|
rlm@0
|
352 Now we can implement a nicer version of the examples from the
|
rlm@0
|
353 [[http://lpsolve.sourceforge.net/][=lp\_solve= website]]. The following is a more or less
|
rlm@0
|
354 line-by-line translation of the Java code from that example.
|
rlm@0
|
355
|
rlm@16
|
356 #+name: farmer-example
|
rlm@0
|
357 #+begin_src clojure :results silent
|
rlm@0
|
358 (in-ns 'pokemon.lpsolve)
|
rlm@0
|
359 (defn farmer-example []
|
rlm@0
|
360 (linear-program
|
rlm@0
|
361 (results
|
rlm@0
|
362 (doto lps
|
rlm@0
|
363 ;; name the columns
|
rlm@0
|
364 (.setColName 1 "wheat")
|
rlm@0
|
365 (.setColName 2 "barley")
|
rlm@0
|
366 (.setAddRowmode true)
|
rlm@0
|
367 ;; row 1 : 120x + 210y <= 15000
|
rlm@0
|
368 (.addConstraintex 2
|
rlm@0
|
369 (double-array [120 210])
|
rlm@0
|
370 (int-array [1 2])
|
rlm@0
|
371 LpSolve/LE
|
rlm@0
|
372 15e3)
|
rlm@0
|
373 ;; row 2 : 110x + 30y <= 4000
|
rlm@0
|
374 (.addConstraintex 2
|
rlm@0
|
375 (double-array [110 30])
|
rlm@0
|
376 (int-array [1 2])
|
rlm@0
|
377 LpSolve/LE
|
rlm@0
|
378 4e3)
|
rlm@0
|
379 ;; ;; row 3 : x + y <= 75
|
rlm@0
|
380 (.addConstraintex 2
|
rlm@0
|
381 (double-array [1 1])
|
rlm@0
|
382 (int-array [1 2])
|
rlm@0
|
383 LpSolve/LE
|
rlm@0
|
384 75)
|
rlm@0
|
385 (.setAddRowmode false)
|
rlm@0
|
386
|
rlm@0
|
387 ;; add constraints
|
rlm@0
|
388 (.setObjFnex 2
|
rlm@0
|
389 (double-array [143 60])
|
rlm@0
|
390 (int-array [1 2]))
|
rlm@0
|
391
|
rlm@0
|
392 ;; set this as a maximization problem
|
rlm@0
|
393 (.setMaxim)))))
|
rlm@0
|
394
|
rlm@0
|
395 #+end_src
|
rlm@0
|
396
|
rlm@0
|
397 #+begin_src clojure :results output :exports both
|
rlm@0
|
398 (clojure.pprint/pprint
|
rlm@0
|
399 (:solution (pokemon.lpsolve/farmer-example)))
|
rlm@0
|
400 #+end_src
|
rlm@0
|
401
|
rlm@0
|
402 #+results:
|
rlm@0
|
403 : {"barley" 53.12499999999999, "wheat" 21.875}
|
rlm@0
|
404
|
rlm@0
|
405 And it works as expected!
|
rlm@0
|
406
|
rlm@0
|
407 *** The Farmer Example in Clojure, Pass 2
|
rlm@0
|
408 We don't have to worry about memory management anymore, and the farmer
|
rlm@0
|
409 example is about half as long as the example from the =LpSolve=
|
rlm@0
|
410 website, but we can still do better. Solving linear problems is all
|
rlm@0
|
411 about the constraint matrix $A$ , the objective function $c$, and the
|
rlm@0
|
412 right-hand-side $b$, plus whatever other options one cares to set for
|
rlm@0
|
413 the particular instance of =lp_solve=. Why not make a version of
|
rlm@0
|
414 =linear-program= that takes care of initialization?
|
rlm@0
|
415
|
rlm@0
|
416
|
rlm@0
|
417
|
rlm@16
|
418 #+name: lp-solve
|
rlm@0
|
419 #+begin_src clojure :results silent
|
rlm@0
|
420 (in-ns 'pokemon.lpsolve)
|
rlm@0
|
421 (defn initialize-lpsolve-row-oriented
|
rlm@0
|
422 "fill in an lpsolve instance using a constraint matrix =A=, the
|
rlm@0
|
423 objective function =c=, and the right-hand-side =b="
|
rlm@0
|
424 [#^LpSolve lps A b c]
|
rlm@0
|
425 ;; set the name of the last column to _something_
|
rlm@0
|
426 ;; this appears to be necessary to ensure proper initialization.
|
rlm@0
|
427 (.setColName lps (count c) (str "C" (count c)))
|
rlm@0
|
428
|
rlm@0
|
429 ;; This is the recommended way to "fill-in" an lps instance from the
|
rlm@0
|
430 ;; documentation. First, set row mode, then set the objective
|
rlm@0
|
431 ;; function, then set each row of the problem, and then turn off row
|
rlm@0
|
432 ;; mode.
|
rlm@0
|
433 (.setAddRowmode lps true)
|
rlm@0
|
434 (.setObjFnex lps (count c)
|
rlm@0
|
435 (double-array c)
|
rlm@0
|
436 (int-array (range 1 (inc (count c)))))
|
rlm@0
|
437 (dorun
|
rlm@0
|
438 (for [n (range (count A))]
|
rlm@0
|
439 (let [row (nth A n)
|
rlm@0
|
440 row-length (int (count row))]
|
rlm@0
|
441 (.addConstraintex lps
|
rlm@0
|
442 row-length
|
rlm@0
|
443 (double-array row)
|
rlm@0
|
444 (int-array (range 1 (inc row-length)))
|
rlm@0
|
445 LpSolve/LE
|
rlm@0
|
446 (double (nth b n))))))
|
rlm@0
|
447 (.setAddRowmode lps false)
|
rlm@0
|
448 lps)
|
rlm@0
|
449
|
rlm@0
|
450
|
rlm@0
|
451 (defmacro lp-solve
|
rlm@0
|
452 "by default:,
|
rlm@0
|
453 minimize (* c x), subject to (<= (* A x) b),
|
rlm@0
|
454 using continuous variables. You may set any number of
|
rlm@0
|
455 other options as in the LpSolve API."
|
rlm@0
|
456 [A b c & lp-solve-forms]
|
rlm@0
|
457 ;; assume that A is a vector of vectors
|
rlm@0
|
458 (concat
|
rlm@0
|
459 (list 'linear-program
|
rlm@0
|
460 (list 'initialize-lpsolve-row-oriented 'lps A b c))
|
rlm@0
|
461 `~lp-solve-forms))
|
rlm@0
|
462 #+end_src
|
rlm@0
|
463
|
rlm@0
|
464 Now, we can use a much more functional approach to solving the
|
rlm@0
|
465 farmer's problem:
|
rlm@0
|
466
|
rlm@16
|
467 #+name: better-farmer
|
rlm@0
|
468 #+begin_src clojure :results silent
|
rlm@0
|
469 (in-ns 'pokemon.lpsolve)
|
rlm@0
|
470 (defn better-farmer-example []
|
rlm@0
|
471 (lp-solve [[120 210]
|
rlm@0
|
472 [110 30]
|
rlm@0
|
473 [1 1]]
|
rlm@0
|
474 [15000
|
rlm@0
|
475 4000
|
rlm@0
|
476 75]
|
rlm@0
|
477 [143 60]
|
rlm@0
|
478 (.setColName lps 1 "wheat")
|
rlm@0
|
479 (.setColName lps 2 "barley")
|
rlm@0
|
480 (.setMaxim lps)
|
rlm@0
|
481 (results lps)))
|
rlm@0
|
482 #+end_src
|
rlm@0
|
483
|
rlm@0
|
484 #+begin_src clojure :exports both :results verbatim
|
rlm@0
|
485 (vec (:solution (pokemon.lpsolve/better-farmer-example)))
|
rlm@0
|
486 #+end_src
|
rlm@0
|
487
|
rlm@0
|
488 #+results:
|
rlm@0
|
489 : [["barley" 53.12499999999999] ["wheat" 21.875]]
|
rlm@0
|
490
|
rlm@0
|
491 Notice that both the inputs to =better-farmer-example= and the results
|
rlm@0
|
492 are immutable.
|
rlm@0
|
493
|
rlm@0
|
494 * Using LpSolve to find Immortal Types
|
rlm@11
|
495 ** Converting the Pok\eacute{}mon problem into a linear form
|
rlm@0
|
496 How can the original question about pok\eacute{}mon types be converted
|
rlm@11
|
497 into a linear problem?
|
rlm@0
|
498
|
rlm@0
|
499 Pokemon types can be considered to be vectors of numbers representing
|
rlm@0
|
500 their susceptances to various attacking types, so Water might look
|
rlm@0
|
501 something like this.
|
rlm@0
|
502
|
rlm@0
|
503 #+begin_src clojure :results scalar :exports both
|
rlm@0
|
504 (:water (pokemon.types/defense-strengths))
|
rlm@0
|
505 #+end_src
|
rlm@0
|
506
|
rlm@0
|
507 #+results:
|
rlm@0
|
508 : [1 0.5 0.5 2 2 0.5 1 1 1 1 1 1 1 1 1 1 0.5]
|
rlm@0
|
509
|
rlm@0
|
510 Where the numbers represent the susceptibility of Water to the
|
rlm@0
|
511 attacking types in the following order:
|
rlm@0
|
512
|
rlm@0
|
513 #+begin_src clojure :results output :exports both
|
rlm@0
|
514 (clojure.pprint/pprint
|
rlm@0
|
515 (pokemon.types/type-names))
|
rlm@0
|
516 #+end_src
|
rlm@0
|
517
|
rlm@0
|
518 #+results:
|
rlm@0
|
519 #+begin_example
|
rlm@0
|
520 [:normal
|
rlm@0
|
521 :fire
|
rlm@0
|
522 :water
|
rlm@0
|
523 :electric
|
rlm@0
|
524 :grass
|
rlm@0
|
525 :ice
|
rlm@0
|
526 :fighting
|
rlm@0
|
527 :poison
|
rlm@0
|
528 :ground
|
rlm@0
|
529 :flying
|
rlm@0
|
530 :psychic
|
rlm@0
|
531 :bug
|
rlm@0
|
532 :rock
|
rlm@0
|
533 :ghost
|
rlm@0
|
534 :dragon
|
rlm@0
|
535 :dark
|
rlm@0
|
536 :steel]
|
rlm@0
|
537 #+end_example
|
rlm@0
|
538
|
rlm@0
|
539
|
rlm@13
|
540 So, for example, Water is resistant (x0.5) against Fire, which is
|
rlm@0
|
541 the second element in the list.
|
rlm@0
|
542
|
rlm@0
|
543 To combine types, these sorts of vectors are multiplied together
|
rlm@0
|
544 pair-wise to yield the resulting combination.
|
rlm@0
|
545
|
rlm@0
|
546 Unfortunately, we need some way to add two type vectors together
|
rlm@0
|
547 instead of multiplying them if we want to solve the problem with
|
rlm@0
|
548 =lp_solve=. Taking the log of the vector does just the trick.
|
rlm@0
|
549
|
rlm@0
|
550 If we make a matrix with each column being the log (base 2) of the
|
rlm@0
|
551 susceptance of each type, then finding an immortal type corresponds to
|
rlm@0
|
552 setting each constraint (the $b$ vector) to -1 (since log_2(1/2) = -1)
|
rlm@0
|
553 and setting the constraint vector $c$ to all ones, which means that we
|
rlm@0
|
554 want to find the immortal type which uses the least amount of types.
|
rlm@0
|
555
|
rlm@16
|
556 #+name: pokemon-lp
|
rlm@0
|
557 #+begin_src clojure :results silent
|
rlm@0
|
558 (in-ns 'pokemon.lpsolve)
|
rlm@0
|
559
|
rlm@0
|
560 (defn log-clamp-matrix [matrix]
|
rlm@0
|
561 ;; we have to clamp the Infinities to a more reasonable negative
|
rlm@0
|
562 ;; value because lp_solve does not play well with infinities in its
|
rlm@0
|
563 ;; constraint matrix.
|
rlm@0
|
564 (map (fn [row] (map #(if (= Double/NEGATIVE_INFINITY %) -1e3 %) row))
|
rlm@0
|
565 (incanter.core/log2
|
rlm@0
|
566 (incanter.core/trans
|
rlm@0
|
567 matrix))))
|
rlm@0
|
568
|
rlm@0
|
569 ;; constraint matrices
|
rlm@0
|
570 (defn log-defense-matrix []
|
rlm@0
|
571 (log-clamp-matrix
|
rlm@0
|
572 (doall (map (pokemon.types/defense-strengths)
|
rlm@0
|
573 (pokemon.types/type-names)))))
|
rlm@0
|
574
|
rlm@0
|
575 (defn log-attack-matrix []
|
rlm@0
|
576 (incanter.core/trans (log-defense-matrix)))
|
rlm@0
|
577
|
rlm@0
|
578 ;; target vectors
|
rlm@0
|
579 (defn all-resistant []
|
rlm@0
|
580 (doall (map (constantly -1) (pokemon.types/type-names))))
|
rlm@0
|
581
|
rlm@0
|
582 (defn all-weak []
|
rlm@0
|
583 (doall (map (constantly 1) (pokemon.types/type-names))))
|
rlm@0
|
584
|
rlm@0
|
585 (defn all-neutral []
|
rlm@0
|
586 (doall (map (constantly 0) (pokemon.types/type-names))))
|
rlm@0
|
587
|
rlm@0
|
588 ;; objective functions
|
rlm@0
|
589 (defn number-of-types []
|
rlm@0
|
590 (doall (map (constantly 1) (pokemon.types/type-names))))
|
rlm@0
|
591
|
rlm@0
|
592 (defn set-constraints
|
rlm@0
|
593 "sets all the constraints for an lpsolve instance to the given
|
rlm@0
|
594 constraint. =constraint= here is one of the LpSolve constants such
|
rlm@0
|
595 as LpSolve/EQ."
|
rlm@0
|
596 [#^LpSolve lps constraint]
|
rlm@0
|
597 (dorun (map (fn [index] (.setConstrType lps index constraint))
|
rlm@0
|
598 ;; ONE based indexing!!!
|
rlm@0
|
599 (range 1 (inc (.getNrows lps))))))
|
rlm@0
|
600
|
rlm@0
|
601
|
rlm@0
|
602 (defn set-discrete
|
rlm@0
|
603 "sets every variable in an lps problem to be a discrete rather than
|
rlm@0
|
604 continuous variable"
|
rlm@0
|
605 [#^LpSolve lps]
|
rlm@0
|
606 (dorun (map (fn [index] (.setInt lps index true))
|
rlm@0
|
607 ;; ONE based indexing!!!
|
rlm@0
|
608 (range 1 (inc (.getNcolumns lps))))))
|
rlm@0
|
609
|
rlm@0
|
610 (defn set-variable-names
|
rlm@0
|
611 "sets the variable names of the problem given a vector of names"
|
rlm@0
|
612 [#^LpSolve lps names]
|
rlm@0
|
613 (dorun
|
rlm@16
|
614 (keep-indexed
|
rlm@16
|
615 (fn [index name]
|
rlm@16
|
616 (.setColName lps (inc index) (str name)))
|
rlm@16
|
617 ;; ONE based indexing!!!
|
rlm@16
|
618 names)))
|
rlm@0
|
619
|
rlm@0
|
620 (defn poke-solve
|
rlm@0
|
621 ([poke-matrix target objective-function constraint min-num-types]
|
rlm@0
|
622 ;; must have at least one type
|
rlm@0
|
623 (let [poke-matrix
|
rlm@0
|
624 (concat poke-matrix
|
rlm@0
|
625 [(map (constantly 1)
|
rlm@0
|
626 (range (count (first poke-matrix))))])
|
rlm@0
|
627 target (concat target [min-num-types])]
|
rlm@0
|
628 (lp-solve poke-matrix target objective-function
|
rlm@0
|
629 (set-constraints lps constraint)
|
rlm@0
|
630 ;; must have more than min-num-types
|
rlm@0
|
631 (.setConstrType lps (count target) LpSolve/GE)
|
rlm@0
|
632 (set-discrete lps)
|
rlm@0
|
633 (set-variable-names lps (pokemon.types/type-names))
|
rlm@0
|
634 (results lps))))
|
rlm@0
|
635 ([poke-matrix target objective-function constraint]
|
rlm@0
|
636 ;; at least one type
|
rlm@0
|
637 (poke-solve poke-matrix target objective-function constraint 1)))
|
rlm@0
|
638
|
rlm@0
|
639 (defn solution
|
rlm@0
|
640 "If the results of an lpsolve operation are feasible, returns the
|
rlm@0
|
641 results. Otherwise, returns the error."
|
rlm@0
|
642 [results]
|
rlm@0
|
643 (if (not (= (:status results) "OPTIMAL"))
|
rlm@0
|
644 (:status results)
|
rlm@0
|
645 (:solution results)))
|
rlm@0
|
646 #+end_src
|
rlm@0
|
647
|
rlm@0
|
648 With this, we are finally able to get some results.
|
rlm@0
|
649
|
rlm@0
|
650 ** Results
|
rlm@16
|
651 #+name: results
|
rlm@0
|
652 #+begin_src clojure :results silent
|
rlm@0
|
653 (in-ns 'pokemon.lpsolve)
|
rlm@0
|
654
|
rlm@0
|
655 (defn best-defense-type
|
rlm@0
|
656 "finds a type combination which is resistant to all attacks."
|
rlm@0
|
657 []
|
rlm@0
|
658 (poke-solve
|
rlm@0
|
659 (log-defense-matrix) (all-resistant) (number-of-types) LpSolve/LE))
|
rlm@0
|
660
|
rlm@0
|
661 (defn worst-attack-type
|
rlm@0
|
662 "finds the attack type which is not-very-effective against all pure
|
rlm@0
|
663 defending types (each single defending type is resistant to this
|
rlm@0
|
664 attack combination"
|
rlm@0
|
665 []
|
rlm@0
|
666 (poke-solve
|
rlm@0
|
667 (log-attack-matrix) (all-resistant) (number-of-types) LpSolve/LE))
|
rlm@0
|
668
|
rlm@0
|
669 (defn worst-defense-type
|
rlm@0
|
670 "finds a defending type that is weak to all single attacking types."
|
rlm@0
|
671 []
|
rlm@0
|
672 (poke-solve
|
rlm@0
|
673 (log-defense-matrix) (all-weak) (number-of-types) LpSolve/GE))
|
rlm@0
|
674
|
rlm@0
|
675 (defn best-attack-type
|
rlm@0
|
676 "finds an attack type which is super effective against all single
|
rlm@0
|
677 defending types"
|
rlm@0
|
678 []
|
rlm@0
|
679 (poke-solve
|
rlm@0
|
680 (log-attack-matrix) (all-weak) (number-of-types) LpSolve/GE))
|
rlm@0
|
681
|
rlm@0
|
682 (defn solid-defense-type
|
rlm@0
|
683 "finds a defense type which is either neutral or resistant to all
|
rlm@0
|
684 single attacking types"
|
rlm@0
|
685 []
|
rlm@0
|
686 (poke-solve
|
rlm@0
|
687 (log-defense-matrix) (all-neutral) (number-of-types) LpSolve/LE))
|
rlm@0
|
688
|
rlm@0
|
689 (defn solid-attack-type
|
rlm@0
|
690 "finds an attack type which is either neutral or super-effective to
|
rlm@0
|
691 all single attacking types."
|
rlm@0
|
692 []
|
rlm@0
|
693 (poke-solve
|
rlm@0
|
694 (log-attack-matrix) (all-neutral) (number-of-types) LpSolve/GE))
|
rlm@0
|
695
|
rlm@0
|
696 (defn weak-defense-type
|
rlm@0
|
697 "finds a defense type which is either neutral or weak to all single
|
rlm@0
|
698 attacking types"
|
rlm@0
|
699 []
|
rlm@0
|
700 (poke-solve
|
rlm@0
|
701 (log-defense-matrix) (all-neutral) (number-of-types) LpSolve/GE))
|
rlm@0
|
702
|
rlm@0
|
703 (defn neutral-defense-type
|
rlm@0
|
704 "finds a defense type which is perfectly neutral to all attacking
|
rlm@0
|
705 types."
|
rlm@0
|
706 []
|
rlm@0
|
707 (poke-solve
|
rlm@0
|
708 (log-defense-matrix) (all-neutral) (number-of-types) LpSolve/EQ))
|
rlm@0
|
709
|
rlm@0
|
710 #+end_src
|
rlm@0
|
711
|
rlm@0
|
712 *** Strongest Attack/Defense Combinations
|
rlm@0
|
713
|
rlm@0
|
714 #+begin_src clojure :results output :exports both
|
rlm@0
|
715 (clojure.pprint/pprint
|
rlm@0
|
716 (pokemon.lpsolve/solution (pokemon.lpsolve/best-defense-type)))
|
rlm@0
|
717 #+end_src
|
rlm@0
|
718
|
rlm@0
|
719 #+results:
|
rlm@0
|
720 #+begin_example
|
rlm@0
|
721 {":normal" 0.0,
|
rlm@0
|
722 ":ground" 1.0,
|
rlm@0
|
723 ":poison" 2.0,
|
rlm@0
|
724 ":flying" 1.0,
|
rlm@0
|
725 ":fighting" 0.0,
|
rlm@0
|
726 ":dragon" 0.0,
|
rlm@0
|
727 ":fire" 0.0,
|
rlm@0
|
728 ":dark" 1.0,
|
rlm@0
|
729 ":ice" 0.0,
|
rlm@0
|
730 ":steel" 1.0,
|
rlm@0
|
731 ":ghost" 0.0,
|
rlm@0
|
732 ":electric" 0.0,
|
rlm@0
|
733 ":bug" 0.0,
|
rlm@0
|
734 ":psychic" 0.0,
|
rlm@0
|
735 ":grass" 0.0,
|
rlm@0
|
736 ":water" 2.0,
|
rlm@0
|
737 ":rock" 0.0}
|
rlm@0
|
738 #+end_example
|
rlm@0
|
739
|
rlm@0
|
740 # #+results-old:
|
rlm@0
|
741 # : [[":normal" 0.0] [":ground" 1.0] [":poison" 0.0] [":flying" 1.0] [":fighting" 0.0] [":dragon" 1.0] [":fire" 0.0] [":dark" 0.0] [":ice" 0.0] [":steel" 2.0] [":ghost" 1.0] [":electric" 0.0] [":bug" 0.0] [":psychic" 0.0] [":grass" 0.0] [":water" 2.0] [":rock" 0.0]]
|
rlm@0
|
742
|
rlm@0
|
743
|
rlm@0
|
744 This is the immortal type combination we've been looking for. By
|
rlm@0
|
745 combining Steel, Water, Poison, and three types which each have complete
|
rlm@0
|
746 immunities to various other types, we've created a type that is resistant to
|
rlm@0
|
747 all attacking types.
|
rlm@0
|
748
|
rlm@0
|
749 #+begin_src clojure :results output :exports both
|
rlm@0
|
750 (clojure.pprint/pprint
|
rlm@0
|
751 (pokemon.types/susceptibility
|
rlm@0
|
752 [:poison :poison :water :water :steel :ground :flying :dark]))
|
rlm@0
|
753 #+end_src
|
rlm@0
|
754
|
rlm@0
|
755 #+results:
|
rlm@0
|
756 #+begin_example
|
rlm@0
|
757 {:water 1/2,
|
rlm@0
|
758 :psychic 0,
|
rlm@0
|
759 :dragon 1/2,
|
rlm@0
|
760 :fire 1/2,
|
rlm@0
|
761 :ice 1/2,
|
rlm@0
|
762 :grass 1/2,
|
rlm@0
|
763 :ghost 1/4,
|
rlm@0
|
764 :poison 0,
|
rlm@0
|
765 :flying 1/2,
|
rlm@0
|
766 :normal 1/2,
|
rlm@0
|
767 :rock 1/2,
|
rlm@0
|
768 :electric 0,
|
rlm@0
|
769 :ground 0,
|
rlm@0
|
770 :fighting 1/2,
|
rlm@0
|
771 :dark 1/4,
|
rlm@0
|
772 :steel 1/8,
|
rlm@0
|
773 :bug 1/8}
|
rlm@0
|
774 #+end_example
|
rlm@0
|
775
|
rlm@0
|
776 # #+results-old:
|
rlm@0
|
777 # : {:water 1/4, :psychic 1/4, :dragon 1/2, :fire 1/2, :ice 1/2, :grass 1/2, :ghost 1/2, :poison 0, :flying 1/4, :normal 0, :rock 1/4, :electric 0, :ground 0, :fighting 0, :dark 1/2, :steel 1/16, :bug 1/16}
|
rlm@0
|
778
|
rlm@0
|
779
|
rlm@0
|
780 Cool!
|
rlm@0
|
781
|
rlm@0
|
782 #+begin_src clojure :results output :exports both
|
rlm@0
|
783 (clojure.pprint/pprint
|
rlm@0
|
784 (pokemon.lpsolve/solution (pokemon.lpsolve/solid-defense-type)))
|
rlm@0
|
785 #+end_src
|
rlm@0
|
786
|
rlm@0
|
787 #+results:
|
rlm@0
|
788 #+begin_example
|
rlm@0
|
789 {":normal" 0.0,
|
rlm@0
|
790 ":ground" 0.0,
|
rlm@0
|
791 ":poison" 0.0,
|
rlm@0
|
792 ":flying" 0.0,
|
rlm@0
|
793 ":fighting" 0.0,
|
rlm@0
|
794 ":dragon" 0.0,
|
rlm@0
|
795 ":fire" 0.0,
|
rlm@0
|
796 ":dark" 1.0,
|
rlm@0
|
797 ":ice" 0.0,
|
rlm@0
|
798 ":steel" 0.0,
|
rlm@0
|
799 ":ghost" 1.0,
|
rlm@0
|
800 ":electric" 0.0,
|
rlm@0
|
801 ":bug" 0.0,
|
rlm@0
|
802 ":psychic" 0.0,
|
rlm@0
|
803 ":grass" 0.0,
|
rlm@0
|
804 ":water" 0.0,
|
rlm@0
|
805 ":rock" 0.0}
|
rlm@0
|
806 #+end_example
|
rlm@0
|
807
|
rlm@0
|
808 Dark and Ghost are the best dual-type combo, and are resistant or
|
rlm@0
|
809 neutral to all types.
|
rlm@0
|
810
|
rlm@0
|
811 #+begin_src clojure :results output :exports both
|
rlm@0
|
812 (clojure.pprint/pprint
|
rlm@0
|
813 (pokemon.types/old-school
|
rlm@0
|
814 (pokemon.lpsolve/solution (pokemon.lpsolve/solid-defense-type))))
|
rlm@0
|
815 #+end_src
|
rlm@0
|
816
|
rlm@0
|
817 #+results:
|
rlm@0
|
818 #+begin_example
|
rlm@0
|
819 {":normal" 0.0,
|
rlm@0
|
820 ":ground" 0.0,
|
rlm@0
|
821 ":poison" 0.0,
|
rlm@0
|
822 ":flying" 0.0,
|
rlm@0
|
823 ":fighting" 0.0,
|
rlm@0
|
824 ":dragon" 0.0,
|
rlm@0
|
825 ":fire" 0.0,
|
rlm@0
|
826 ":ice" 0.0,
|
rlm@0
|
827 ":ghost" 1.0,
|
rlm@0
|
828 ":electric" 0.0,
|
rlm@0
|
829 ":bug" 0.0,
|
rlm@0
|
830 ":psychic" 1.0,
|
rlm@0
|
831 ":grass" 0.0,
|
rlm@0
|
832 ":water" 0.0,
|
rlm@0
|
833 ":rock" 0.0}
|
rlm@0
|
834 #+end_example
|
rlm@0
|
835
|
rlm@0
|
836 Ghost and Psychic are a powerful dual type combo in the original games,
|
rlm@0
|
837 due to a glitch which made Psychic immune to Ghost type attacks, even
|
rlm@14
|
838 though the game claims that Ghost is strong against Psychic.
|
rlm@0
|
839
|
rlm@0
|
840 #+begin_src clojure :results verbatim :exports both
|
rlm@0
|
841 (pokemon.lpsolve/solution (pokemon.lpsolve/best-attack-type))
|
rlm@0
|
842 #+end_src
|
rlm@0
|
843
|
rlm@0
|
844 #+results:
|
rlm@0
|
845 : INFEASIBLE
|
rlm@0
|
846
|
rlm@0
|
847 #+begin_src clojure :results verbatim :exports both
|
rlm@0
|
848 (pokemon.lpsolve/solution (pokemon.lpsolve/solid-attack-type))
|
rlm@0
|
849 #+end_src
|
rlm@0
|
850
|
rlm@0
|
851 #+results:
|
rlm@0
|
852 : INFEASIBLE
|
rlm@0
|
853
|
rlm@0
|
854
|
rlm@0
|
855 #+begin_src clojure :results verbatim :exports both
|
rlm@0
|
856 (pokemon.types/old-school
|
rlm@0
|
857 (pokemon.lpsolve/solution (pokemon.lpsolve/best-attack-type)))
|
rlm@0
|
858 #+end_src
|
rlm@0
|
859
|
rlm@0
|
860 #+results:
|
rlm@0
|
861 : INFEASIBLE
|
rlm@0
|
862
|
rlm@0
|
863
|
rlm@0
|
864 #+begin_src clojure :results output :exports both
|
rlm@0
|
865 (clojure.pprint/pprint
|
rlm@0
|
866 (pokemon.types/old-school
|
rlm@0
|
867 (pokemon.lpsolve/solution (pokemon.lpsolve/solid-attack-type))))
|
rlm@0
|
868 #+end_src
|
rlm@0
|
869
|
rlm@0
|
870 #+results:
|
rlm@0
|
871 #+begin_example
|
rlm@0
|
872 {":normal" 0.0,
|
rlm@0
|
873 ":ground" 0.0,
|
rlm@0
|
874 ":poison" 0.0,
|
rlm@0
|
875 ":flying" 0.0,
|
rlm@0
|
876 ":fighting" 0.0,
|
rlm@0
|
877 ":dragon" 1.0,
|
rlm@0
|
878 ":fire" 0.0,
|
rlm@0
|
879 ":ice" 0.0,
|
rlm@0
|
880 ":ghost" 0.0,
|
rlm@0
|
881 ":electric" 0.0,
|
rlm@0
|
882 ":bug" 0.0,
|
rlm@0
|
883 ":psychic" 0.0,
|
rlm@0
|
884 ":grass" 0.0,
|
rlm@0
|
885 ":water" 0.0,
|
rlm@0
|
886 ":rock" 0.0}
|
rlm@0
|
887 #+end_example
|
rlm@0
|
888
|
rlm@11
|
889 The best attacking type combination is Dragon from the original games.
|
rlm@11
|
890 It is neutral against all the original types except for Dragon, which
|
rlm@11
|
891 it is strong against. There is no way to make an attacking type that
|
rlm@11
|
892 is strong against every type, or even one that is strong or neutral
|
rlm@11
|
893 against every type, in the new games.
|
rlm@0
|
894
|
rlm@0
|
895
|
rlm@0
|
896 *** Weakest Attack/Defense Combinations
|
rlm@0
|
897
|
rlm@0
|
898 #+begin_src clojure :results output :exports both
|
rlm@0
|
899 (clojure.pprint/pprint
|
rlm@0
|
900 (pokemon.types/old-school
|
rlm@0
|
901 (pokemon.lpsolve/solution (pokemon.lpsolve/worst-attack-type))))
|
rlm@0
|
902 #+end_src
|
rlm@0
|
903
|
rlm@0
|
904 #+results:
|
rlm@0
|
905 #+begin_example
|
rlm@0
|
906 {":normal" 5.0,
|
rlm@0
|
907 ":ground" 0.0,
|
rlm@0
|
908 ":poison" 0.0,
|
rlm@0
|
909 ":flying" 0.0,
|
rlm@0
|
910 ":fighting" 0.0,
|
rlm@0
|
911 ":dragon" 0.0,
|
rlm@0
|
912 ":fire" 1.0,
|
rlm@0
|
913 ":ice" 2.0,
|
rlm@0
|
914 ":ghost" 1.0,
|
rlm@0
|
915 ":electric" 1.0,
|
rlm@0
|
916 ":bug" 1.0,
|
rlm@0
|
917 ":psychic" 0.0,
|
rlm@0
|
918 ":grass" 3.0,
|
rlm@0
|
919 ":water" 2.0,
|
rlm@0
|
920 ":rock" 0.0}
|
rlm@0
|
921 #+end_example
|
rlm@0
|
922
|
rlm@0
|
923 # #+results-old:
|
rlm@0
|
924 # : [[":normal" 5.0] [":ground" 1.0] [":poison" 0.0] [":flying" 0.0] [":fighting" 2.0] [":dragon" 0.0] [":fire" 0.0] [":ice" 4.0] [":ghost" 1.0] [":electric" 4.0] [":bug" 0.0] [":psychic" 0.0] [":grass" 0.0] [":water" 1.0] [":rock" 1.0]]
|
rlm@0
|
925
|
rlm@0
|
926 #+begin_src clojure :results output :exports both
|
rlm@0
|
927 (clojure.pprint/pprint
|
rlm@0
|
928 (pokemon.lpsolve/solution (pokemon.lpsolve/worst-attack-type)))
|
rlm@0
|
929 #+end_src
|
rlm@0
|
930
|
rlm@0
|
931 #+results:
|
rlm@0
|
932 #+begin_example
|
rlm@0
|
933 {":normal" 4.0,
|
rlm@0
|
934 ":ground" 1.0,
|
rlm@0
|
935 ":poison" 1.0,
|
rlm@0
|
936 ":flying" 0.0,
|
rlm@0
|
937 ":fighting" 1.0,
|
rlm@0
|
938 ":dragon" 0.0,
|
rlm@0
|
939 ":fire" 0.0,
|
rlm@0
|
940 ":dark" 0.0,
|
rlm@0
|
941 ":ice" 4.0,
|
rlm@0
|
942 ":steel" 0.0,
|
rlm@0
|
943 ":ghost" 1.0,
|
rlm@0
|
944 ":electric" 3.0,
|
rlm@0
|
945 ":bug" 0.0,
|
rlm@0
|
946 ":psychic" 1.0,
|
rlm@0
|
947 ":grass" 1.0,
|
rlm@0
|
948 ":water" 1.0,
|
rlm@0
|
949 ":rock" 2.0}
|
rlm@0
|
950 #+end_example
|
rlm@0
|
951
|
rlm@0
|
952 # #+results-old:
|
rlm@0
|
953 # : [[":normal" 4.0] [":ground" 1.0] [":poison" 1.0] [":flying" 0.0] [":fighting" 2.0] [":dragon" 0.0] [":fire" 0.0] [":dark" 0.0] [":ice" 5.0] [":steel" 0.0] [":ghost" 1.0] [":electric" 5.0] [":bug" 0.0] [":psychic" 1.0] [":grass" 0.0] [":water" 1.0] [":rock" 2.0]]
|
rlm@0
|
954
|
rlm@0
|
955
|
rlm@0
|
956 This is an extremely interesting type combination, in that it uses
|
rlm@0
|
957 quite a few types.
|
rlm@0
|
958
|
rlm@0
|
959 #+begin_src clojure :results verbatim :exports both
|
rlm@0
|
960 (reduce + (vals (:solution (pokemon.lpsolve/worst-attack-type))))
|
rlm@0
|
961 #+end_src
|
rlm@0
|
962
|
rlm@0
|
963 #+results:
|
rlm@0
|
964 : 20.0
|
rlm@0
|
965
|
rlm@0
|
966 20 types is the /minimum/ number of types before the attacking
|
rlm@0
|
967 combination is not-very-effective or worse against all defending
|
rlm@0
|
968 types. This would probably have been impossible to discover using
|
rlm@0
|
969 best-first search, since it involves such an intricate type
|
rlm@0
|
970 combination.
|
rlm@0
|
971
|
rlm@0
|
972 It's so interesting that it takes 20 types to make an attack type that
|
rlm@11
|
973 is weak to all types that the combination merits further
|
rlm@11
|
974 investigation.
|
rlm@0
|
975
|
rlm@0
|
976 Unfortunately, all of the tools that we've written so far are focused
|
rlm@0
|
977 on defense type combinations. However, it is possible to make every
|
rlm@0
|
978 tool attack-oriented via a simple macro.
|
rlm@0
|
979
|
rlm@16
|
980 #+name: attack-oriented
|
rlm@0
|
981 #+begin_src clojure :results silent
|
rlm@0
|
982 (in-ns 'pokemon.lpsolve)
|
rlm@0
|
983
|
rlm@0
|
984 (defmacro attack-mode [& forms]
|
rlm@0
|
985 `(let [attack-strengths# pokemon.types/attack-strengths
|
rlm@0
|
986 defense-strengths# pokemon.types/defense-strengths]
|
rlm@0
|
987 (binding [pokemon.types/attack-strengths
|
rlm@0
|
988 defense-strengths#
|
rlm@0
|
989 pokemon.types/defense-strengths
|
rlm@0
|
990 attack-strengths#]
|
rlm@0
|
991 ~@forms)))
|
rlm@0
|
992 #+end_src
|
rlm@0
|
993
|
rlm@0
|
994 Now all the tools from =pokemon.types= will work for attack
|
rlm@0
|
995 combinations.
|
rlm@0
|
996
|
rlm@0
|
997 #+begin_src clojure :results output :exports both
|
rlm@0
|
998 (clojure.pprint/pprint
|
rlm@0
|
999 (pokemon.types/susceptibility [:water]))
|
rlm@0
|
1000 #+end_src
|
rlm@0
|
1001
|
rlm@0
|
1002 #+results:
|
rlm@0
|
1003 #+begin_example
|
rlm@0
|
1004 {:water 1/2,
|
rlm@0
|
1005 :psychic 1,
|
rlm@0
|
1006 :dragon 1,
|
rlm@0
|
1007 :fire 1/2,
|
rlm@0
|
1008 :ice 1/2,
|
rlm@0
|
1009 :grass 2,
|
rlm@0
|
1010 :ghost 1,
|
rlm@0
|
1011 :poison 1,
|
rlm@0
|
1012 :flying 1,
|
rlm@0
|
1013 :normal 1,
|
rlm@0
|
1014 :rock 1,
|
rlm@0
|
1015 :electric 2,
|
rlm@0
|
1016 :ground 1,
|
rlm@0
|
1017 :fighting 1,
|
rlm@0
|
1018 :dark 1,
|
rlm@0
|
1019 :steel 1/2,
|
rlm@0
|
1020 :bug 1}
|
rlm@0
|
1021 #+end_example
|
rlm@0
|
1022
|
rlm@0
|
1023
|
rlm@0
|
1024 #+begin_src clojure :results output :exports both
|
rlm@0
|
1025 (clojure.pprint/pprint
|
rlm@0
|
1026 (pokemon.lpsolve/attack-mode
|
rlm@0
|
1027 (pokemon.types/susceptibility [:water])))
|
rlm@0
|
1028 #+end_src
|
rlm@0
|
1029
|
rlm@0
|
1030 #+results:
|
rlm@0
|
1031 #+begin_example
|
rlm@0
|
1032 {:water 1/2,
|
rlm@0
|
1033 :psychic 1,
|
rlm@0
|
1034 :dragon 1/2,
|
rlm@0
|
1035 :fire 2,
|
rlm@0
|
1036 :ice 1,
|
rlm@0
|
1037 :grass 1/2,
|
rlm@0
|
1038 :ghost 1,
|
rlm@0
|
1039 :poison 1,
|
rlm@0
|
1040 :flying 1,
|
rlm@0
|
1041 :normal 1,
|
rlm@0
|
1042 :rock 2,
|
rlm@0
|
1043 :electric 1,
|
rlm@0
|
1044 :ground 2,
|
rlm@0
|
1045 :fighting 1,
|
rlm@0
|
1046 :dark 1,
|
rlm@0
|
1047 :steel 1,
|
rlm@0
|
1048 :bug 1}
|
rlm@0
|
1049 #+end_example
|
rlm@0
|
1050
|
rlm@0
|
1051 Now =pokemon.types/susceptibility= reports the /attack-type/
|
rlm@0
|
1052 combination's effectiveness against other types.
|
rlm@0
|
1053
|
rlm@0
|
1054 The 20 type combo achieves its goal in a very clever way.
|
rlm@0
|
1055
|
rlm@0
|
1056 First, it weakens its effectiveness to other types at the expense of
|
rlm@0
|
1057 making it very strong against flying.
|
rlm@0
|
1058
|
rlm@0
|
1059 #+begin_src clojure :results output :exports both
|
rlm@0
|
1060 (clojure.pprint/pprint
|
rlm@0
|
1061 (pokemon.lpsolve/attack-mode
|
rlm@0
|
1062 (pokemon.types/susceptibility
|
rlm@0
|
1063 [:normal :normal :normal :normal
|
rlm@0
|
1064 :ice :ice :ice :ice
|
rlm@0
|
1065 :electric :electric :electric
|
rlm@0
|
1066 :rock :rock])))
|
rlm@0
|
1067 #+end_src
|
rlm@0
|
1068
|
rlm@0
|
1069 #+results:
|
rlm@0
|
1070 #+begin_example
|
rlm@0
|
1071 {:water 1/2,
|
rlm@0
|
1072 :psychic 1,
|
rlm@0
|
1073 :dragon 2,
|
rlm@0
|
1074 :fire 1/4,
|
rlm@0
|
1075 :ice 1/4,
|
rlm@0
|
1076 :grass 2,
|
rlm@0
|
1077 :ghost 0,
|
rlm@0
|
1078 :poison 1,
|
rlm@0
|
1079 :flying 512,
|
rlm@0
|
1080 :normal 1,
|
rlm@0
|
1081 :rock 1/16,
|
rlm@0
|
1082 :electric 1/8,
|
rlm@0
|
1083 :ground 0,
|
rlm@0
|
1084 :fighting 1/4,
|
rlm@0
|
1085 :dark 1,
|
rlm@0
|
1086 :steel 1/1024,
|
rlm@0
|
1087 :bug 4}
|
rlm@0
|
1088 #+end_example
|
rlm@0
|
1089
|
rlm@0
|
1090 Then, it removes it's strengths against Flying, Normal, and Fighting
|
rlm@0
|
1091 by adding Ghost and Ground.
|
rlm@0
|
1092
|
rlm@0
|
1093 #+begin_src clojure :results output :exports both
|
rlm@0
|
1094 (clojure.pprint/pprint
|
rlm@0
|
1095 (pokemon.lpsolve/attack-mode
|
rlm@0
|
1096 (pokemon.types/susceptibility
|
rlm@0
|
1097 [:normal :normal :normal :normal
|
rlm@0
|
1098 :ice :ice :ice :ice
|
rlm@0
|
1099 :electric :electric :electric
|
rlm@0
|
1100 :rock :rock
|
rlm@0
|
1101 ;; Spot resistances
|
rlm@0
|
1102 :ghost :ground])))
|
rlm@0
|
1103 #+end_src
|
rlm@0
|
1104
|
rlm@0
|
1105 #+results:
|
rlm@0
|
1106 #+begin_example
|
rlm@0
|
1107 {:water 1/2,
|
rlm@0
|
1108 :psychic 2,
|
rlm@0
|
1109 :dragon 2,
|
rlm@0
|
1110 :fire 1/2,
|
rlm@0
|
1111 :ice 1/4,
|
rlm@0
|
1112 :grass 1,
|
rlm@0
|
1113 :ghost 0,
|
rlm@0
|
1114 :poison 2,
|
rlm@0
|
1115 :flying 0,
|
rlm@0
|
1116 :normal 0,
|
rlm@0
|
1117 :rock 1/8,
|
rlm@0
|
1118 :electric 1/4,
|
rlm@0
|
1119 :ground 0,
|
rlm@0
|
1120 :fighting 1/4,
|
rlm@0
|
1121 :dark 1/2,
|
rlm@0
|
1122 :steel 1/1024,
|
rlm@0
|
1123 :bug 2}
|
rlm@0
|
1124 #+end_example
|
rlm@0
|
1125
|
rlm@0
|
1126 Adding the pair Psychic and Fighting takes care of its strength
|
rlm@0
|
1127 against Psychic and makes it ineffective against Dark, which is immune
|
rlm@0
|
1128 to Psychic.
|
rlm@0
|
1129
|
rlm@0
|
1130 Adding the pair Grass and Poison makes takes care of its strength
|
rlm@0
|
1131 against poison and makes it ineffective against Steel, which is immune
|
rlm@0
|
1132 to poison.
|
rlm@0
|
1133
|
rlm@0
|
1134 #+begin_src clojure :results output :exports both
|
rlm@0
|
1135 (clojure.pprint/pprint
|
rlm@0
|
1136 (pokemon.lpsolve/attack-mode
|
rlm@0
|
1137 (pokemon.types/susceptibility
|
rlm@0
|
1138 [;; setup
|
rlm@0
|
1139 :normal :normal :normal :normal
|
rlm@0
|
1140 :ice :ice :ice :ice
|
rlm@0
|
1141 :electric :electric :electric
|
rlm@0
|
1142 :rock :rock
|
rlm@0
|
1143 ;; Spot resistances
|
rlm@0
|
1144 :ghost :ground
|
rlm@0
|
1145 ;; Pair resistances
|
rlm@0
|
1146 :psychic :fighting
|
rlm@0
|
1147 :grass :poison])))
|
rlm@0
|
1148 #+end_src
|
rlm@0
|
1149
|
rlm@0
|
1150 #+results:
|
rlm@0
|
1151 #+begin_example
|
rlm@0
|
1152 {:water 1,
|
rlm@0
|
1153 :psychic 1/2,
|
rlm@0
|
1154 :dragon 1,
|
rlm@0
|
1155 :fire 1/4,
|
rlm@0
|
1156 :ice 1/2,
|
rlm@0
|
1157 :grass 1,
|
rlm@0
|
1158 :ghost 0,
|
rlm@0
|
1159 :poison 1/2,
|
rlm@0
|
1160 :flying 0,
|
rlm@0
|
1161 :normal 0,
|
rlm@0
|
1162 :rock 1/4,
|
rlm@0
|
1163 :electric 1/4,
|
rlm@0
|
1164 :ground 0,
|
rlm@0
|
1165 :fighting 1/2,
|
rlm@0
|
1166 :dark 0,
|
rlm@0
|
1167 :steel 0,
|
rlm@0
|
1168 :bug 1/2}
|
rlm@0
|
1169 #+end_example
|
rlm@0
|
1170
|
rlm@0
|
1171 Can you see the final step?
|
rlm@0
|
1172
|
rlm@13
|
1173 It's adding the Water type, which is weak against Water, Dragon, and
|
rlm@13
|
1174 Grass and strong against Rock and Fire.
|
rlm@0
|
1175
|
rlm@0
|
1176 #+begin_src clojure :results output :exports both
|
rlm@0
|
1177 (clojure.pprint/pprint
|
rlm@0
|
1178 (pokemon.lpsolve/attack-mode
|
rlm@0
|
1179 (pokemon.types/susceptibility
|
rlm@0
|
1180 [;; setup
|
rlm@0
|
1181 :normal :normal :normal :normal
|
rlm@0
|
1182 :ice :ice :ice :ice
|
rlm@0
|
1183 :electric :electric :electric
|
rlm@0
|
1184 :rock :rock
|
rlm@0
|
1185 ;; Spot resistances
|
rlm@0
|
1186 :ghost :ground
|
rlm@0
|
1187 ;; Pair resistances
|
rlm@0
|
1188 :psychic :fighting
|
rlm@0
|
1189 :grass :poison
|
rlm@0
|
1190 ;; completion
|
rlm@0
|
1191 :water])))
|
rlm@0
|
1192 #+end_src
|
rlm@0
|
1193
|
rlm@0
|
1194 #+results:
|
rlm@0
|
1195 #+begin_example
|
rlm@0
|
1196 {:water 1/2,
|
rlm@0
|
1197 :psychic 1/2,
|
rlm@0
|
1198 :dragon 1/2,
|
rlm@0
|
1199 :fire 1/2,
|
rlm@0
|
1200 :ice 1/2,
|
rlm@0
|
1201 :grass 1/2,
|
rlm@0
|
1202 :ghost 0,
|
rlm@0
|
1203 :poison 1/2,
|
rlm@0
|
1204 :flying 0,
|
rlm@0
|
1205 :normal 0,
|
rlm@0
|
1206 :rock 1/2,
|
rlm@0
|
1207 :electric 1/4,
|
rlm@0
|
1208 :ground 0,
|
rlm@0
|
1209 :fighting 1/2,
|
rlm@0
|
1210 :dark 0,
|
rlm@0
|
1211 :steel 0,
|
rlm@0
|
1212 :bug 1/2}
|
rlm@0
|
1213 #+end_example
|
rlm@0
|
1214
|
rlm@0
|
1215 Which makes a particularly beautiful combination which is ineffective
|
rlm@0
|
1216 against all defending types.
|
rlm@0
|
1217
|
rlm@0
|
1218
|
rlm@0
|
1219 # #+begin_src clojure :results scalar :exports both
|
rlm@0
|
1220 # (with-out-str (clojure.contrib.pprint/pprint (seq (attack-mode (pokemon.types/susceptibility [:normal :normal :normal :normal :ice :ice :ice :ice :electric :electric :electric :rock :rock :ground :ghost :psychic :fighting :grass :poison])))))
|
rlm@0
|
1221 # #+end_src
|
rlm@0
|
1222
|
rlm@0
|
1223 # #+results:
|
rlm@0
|
1224 # | [:water 1] | [:psychic 1/2] | [:dragon 1] | [:fire 1/4] | [:ice 1/2] | [:grass 1] | [:ghost 0] | [:poison 1/2] | [:flying 0] | [:normal 0] | [:rock 1/4] | [:electric 1/4] | [:ground 0] | [:fighting 1/2] | [:dark 0] | [:steel 0] | [:bug 1/2] |
|
rlm@0
|
1225
|
rlm@0
|
1226
|
rlm@0
|
1227 Is there anything else that's interesting?
|
rlm@0
|
1228
|
rlm@0
|
1229 #+begin_src clojure :exports both
|
rlm@0
|
1230 (pokemon.lpsolve/solution (pokemon.lpsolve/worst-defense-type))
|
rlm@0
|
1231 #+end_src
|
rlm@0
|
1232
|
rlm@0
|
1233 #+results:
|
rlm@0
|
1234 : INFEASIBLE
|
rlm@0
|
1235
|
rlm@0
|
1236 #+begin_src clojure :exports both
|
rlm@0
|
1237 (pokemon.types/old-school
|
rlm@0
|
1238 (pokemon.lpsolve/solution (pokemon.lpsolve/worst-defense-type)))
|
rlm@0
|
1239 #+end_src
|
rlm@0
|
1240
|
rlm@0
|
1241 #+results:
|
rlm@0
|
1242 : INFEASIBLE
|
rlm@0
|
1243
|
rlm@0
|
1244 #+begin_src clojure :exports both
|
rlm@0
|
1245 (pokemon.lpsolve/solution (pokemon.lpsolve/weak-defense-type))
|
rlm@0
|
1246 #+end_src
|
rlm@0
|
1247
|
rlm@0
|
1248 #+results:
|
rlm@0
|
1249 : INFEASIBLE
|
rlm@0
|
1250
|
rlm@0
|
1251 #+begin_src clojure :exports both
|
rlm@0
|
1252 (pokemon.types/old-school
|
rlm@0
|
1253 (pokemon.lpsolve/solution (pokemon.lpsolve/weak-defense-type)))
|
rlm@0
|
1254 #+end_src
|
rlm@0
|
1255
|
rlm@0
|
1256 #+results:
|
rlm@0
|
1257 : INFEASIBLE
|
rlm@0
|
1258
|
rlm@0
|
1259 #+begin_src clojure :exports both
|
rlm@0
|
1260 (pokemon.lpsolve/solution (pokemon.lpsolve/neutral-defense-type))
|
rlm@0
|
1261 #+end_src
|
rlm@0
|
1262
|
rlm@0
|
1263 #+results:
|
rlm@0
|
1264 : INFEASIBLE
|
rlm@0
|
1265
|
rlm@0
|
1266 #+begin_src clojure :exports both
|
rlm@0
|
1267 (pokemon.types/old-school
|
rlm@0
|
1268 (pokemon.lpsolve/solution (pokemon.lpsolve/neutral-defense-type)))
|
rlm@0
|
1269 #+end_src
|
rlm@0
|
1270
|
rlm@0
|
1271 #+results:
|
rlm@0
|
1272 : INFEASIBLE
|
rlm@0
|
1273
|
rlm@0
|
1274 There is no way to produce a defense-type that is weak to all types.
|
rlm@0
|
1275 This is probably because there are many types that are completely
|
rlm@0
|
1276 immune to some types, such as Flying, which is immune to Ground. A
|
rlm@0
|
1277 perfectly weak type could not use any of these types.
|
rlm@0
|
1278
|
rlm@0
|
1279 * Summary
|
rlm@0
|
1280
|
rlm@14
|
1281 Overall, the pok\eacute{}mon type system is slanted towards defense
|
rlm@14
|
1282 rather than offense. While it is possible to create superior
|
rlm@11
|
1283 defensive types and exceptionally weak attack types, it is not
|
rlm@11
|
1284 possible to create exceptionally weak defensive types or very powerful
|
rlm@11
|
1285 attack types.
|
rlm@0
|
1286
|
rlm@0
|
1287 Using the =lp_solve= library was more complicated than the best-first
|
rlm@0
|
1288 search, but yielded results quickly and efficiently. Expressing the
|
rlm@0
|
1289 problem in a linear form does have its drawbacks, however --- it's
|
rlm@0
|
1290 hard to ask questions such as "what is the best 3-type defensive combo
|
rlm@0
|
1291 in terms of susceptibility?", since susceptibility is not a linear
|
rlm@0
|
1292 function of a combo's types. It is also hard to get all the solutions
|
rlm@0
|
1293 to a particular problem, such as all the pokemon type combinations of
|
rlm@0
|
1294 length 8 which are immortal defense types.
|
rlm@0
|
1295
|
rlm@0
|
1296 * COMMENT main-program
|
rlm@0
|
1297 #+begin_src clojure :tangle ../src/pokemon/lpsolve.clj :noweb yes :exports none
|
rlm@0
|
1298 <<intro>>
|
rlm@0
|
1299 <<body>>
|
rlm@0
|
1300 <<declares>>
|
rlm@0
|
1301 <<memory-management>>
|
rlm@0
|
1302 <<get-results>>
|
rlm@0
|
1303 <<solve>>
|
rlm@0
|
1304 <<farmer-example>>
|
rlm@0
|
1305 <<lp-solve>>
|
rlm@0
|
1306 <<better-farmer>>
|
rlm@0
|
1307 <<pokemon-lp>>
|
rlm@0
|
1308 <<results>>
|
rlm@0
|
1309 <<attack-oriented>>
|
rlm@0
|
1310 #+end_src
|
rlm@0
|
1311
|
rlm@0
|
1312
|
rlm@0
|
1313
|