AUTOMATED REASONING. Agostino Dovier. Udine, December Università di Udine CLPLAB
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1 AUTOMATED REASONING Agostino Dovier Università di Udine CLPLAB Udine, December 2016 AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
2 THE HANOI TOWER AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
3 THE HANOI TOWER AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
4 THE HANOI TOWER Representation using inpeg(time, disk, peg) and on(time, disk above, disk below/floor). The top(time, peg, disk) is defined from the other predicates. peg(1..3). disk(1..n). tempo(0..t). % Initial state (you can use others) inpeg(0,d,1) :- disk(d). on(0,d,d+1) :- disk(d),disk(d+1). on(0,n,floor). % Goal state (all in the 2nd peg) goal(d) :- inpeg(t,d,2), disk(d). :- disk(d), not goal(d). AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
5 THE HANOI TOWER Representation using inpeg(time, disk, peg) and on(time, disk above, disk below/floor). The top(time, peg, disk) is defined from the other predicates. peg(1..3). disk(1..n). tempo(0..t). % Initial state (you can use others) inpeg(0,d,1) :- disk(d). on(0,d,d+1) :- disk(d),disk(d+1). on(0,n,floor). % Goal state (all in the 2nd peg) goal(d) :- inpeg(t,d,2), disk(d). :- disk(d), not goal(d). AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
6 HANOI TOWER Action: move(time,pegx, pegy) % There is one and only one move at time T 1{ move(t,x,y): peg(x), peg(y), X!= Y} 1 :- tempo(t), T < t. % Smaller above :- on(t,a,b), tempo(t), disk(a), disk(b), A >= B. % If there are no disks, no moves :- move(t,a,b), empty(t,a), tempo(t), peg(a), peg(b). AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
7 HANOI TOWER Auxiliary predicates: covered(t,d2) :- on(t,d1,d2), tempo(t), disk(d1), disk(d2). top(t,a,d) :- inpeg(t,d,a), not covered(t,d), tempo(t), disk(d), peg(a). nonempty(t,a) :- inpeg(t,d,a), tempo(t), disk(d), peg(a). empty(t,a) :- not nonempty(t,a), tempo(t), peg(a). top(t,a,floor) :- empty(t,a), tempo(t), peg(a). moved(t,d) :- top(t,a,d), move(t,a,b), tempo(t), disk(d), peg(a), peg(b). AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
8 HANOI TOWER % 1. change on of moved disk on(t+1,d1,d2) :- top(t,a,d1), top(t,b,d2), move(t,a,b), tempo(t), tempo(t+1), peg(a), peg(b), disk(d1), disk(d2). on(t+1,d,floor) :- top(t,a,d), move(t,a,b), empty(t,b), tempo(t), tempo(t+1), peg(a), peg(b), disk(d). % 2. change inpeg of moved disk inpeg(t+1,d,b) :- top(t,a,d), move(t,a,b), tempo(t), tempo(t+1), peg(a), peg(b),disk(d). % Inertia on(t+1,d,floor) :- on(t,d,floor), not moved(t,d), tempo(t), tempo(t+1), disk(d). on(t+1,d1,d2) :- on(t,d1,d2), not moved(t,d1), tempo(t), tempo(t+1), disk(d1), disk(d2). inpeg(t+1,d,a) :- inpeg(t,d,a), not moved(t,d), tempo(t), tempo(t+1), peg(a), disk(d). AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
9 SAM LLOYD S PUZZLE AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
10 SAM LLOYD S PUZZLE tempo(0..t). val(0..8). range(0..2). % % X=0 % % X=1 % % X=2 %%%%%%% % <- Y %%%%%% %% "0" is the empty cell (the hole) %% Define the predicate %% cell(time T, row X, column Y, value V) %%% Input (example) cell(0,0,0,1). cell(0,0,1,2). cell(0,0,2,5). cell(0,1,0,3). cell(0,1,1,4). cell(0,1,2,8). cell(0,2,0,6). cell(0,2,1,0). cell(0,2,2,7). %%% Goal goal(x,y) :- range(x), range(y), cell(t,x,y,3*x+y). :- range(x),range(y), not goal(x,y). AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
11 SAM LLOYD S PUZZLE %%% The move moves the hole 1{ move(t,up); move(t,down); move(t,left); move(t,right)}1 :- tempo(t), tempo(t+1). hole(t,x,y) :- cell(t,x,y,0), tempo(t), range(x), range(y). % Forbidden moves :- tempo(t), move(t,up), range(y), hole(t,0,y). :- tempo(t), move(t,down), range(y), hole(t,2,y). :- tempo(t), move(t,left), range(x), hole(t,x,0). :- tempo(t), move(t,right), range(y), hole(t,x,2). % New position for the hole moved(t,x-1,y) :- hole(t,x,y), move(t,up), tempo(t),range(x),range(y). moved(t,x+1,y) :- hole(t,x,y), move(t,down), tempo(t),range(x),range(y). moved(t,x,y-1) :- hole(t,x,y), move(t,left), tempo(t),range(x),range(y). moved(t,x,y+1) :- hole(t,x,y), move(t,right), tempo(t),range(x),range(y). AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
12 SAM LLOYD S PUZZLE % New cell contents cell(t+1,x,y,0) :- moved(t,x,y), tempo(t), tempo(t+1), range(x), range(y). cell(t+1,x1,y1,v) :- hole(t,x1,y1), moved(t,x2,y2), cell(t,x2,y2,v), tempo(t), tempo(t+1), val(v), range(x1), range(x2), range(y1), range(y2). % Inertia affected(t,x,y) :- hole(t,x,y), tempo(t), range(x), range(y). affected(t,x,y) :- moved(t,x,y), tempo(t), range(x), range(y). cell(t+1,x,y,v) :- cell(t,x,y,v), not affected(t,x,y), tempo(t), tempo(t+1), range(x), range(y), val(v). AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
13 SOKOBAN RULES Sokoban is a puzzle invented by Hiroyuki Imabayashi in 1980 Sokoban means significa warehouseman (magazziniere) in Japanese It is one of the first videogames. It has only three rules. AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
14 SOKOBAN REPRESENTATION top(c2r5,c2r4). right(c3r2,c4r2). right(c3r6,c4r6). top(c2r6,c2r5). right(c4r2,c5r2). right(c4r6,c5r6). top(c3r3,c3r2). right(c5r2,c6r2). top(c3r4,c3r3). right(c6r3,c7r3). box(c6r3). top(c3r5,c3r4). right(c2r4,c3r4). box(c5r4). top(c3r6,c3r5). right(c3r4,c4r4). box(c5r5). top(c5r5,c5r4). right(c4r4,c5r4). top(c5r6,c5r5). right(c5r4,c6r4). storage(c3r3). top(c6r3,c6r2). right(c6r4,c7r4). storage(c3r4). top(c6r4,c6r3). right(c2r5,c3r5). storage(c4r4). top(c6r5,c6r4). right(c5r5,c6r5). top(c7r4,c7r3). right(c6r5,c7r5). sokoban(c4r6). top(c7r5,c7r4). right(c2r6,c3r6). Solve it defining the predicate push(source cell,direction,destination cell), where direction is up, down, left, right. AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
15 PEG SOLITAIRE AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
16 RUBIK S CUBE AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
17 RUBIK S CUBE AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
18 BRAINTWIST AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
19 12 COINS I HAVE NOT A PROGRAM FOR IT! There are 12 coins Exactly one of them is false The false one weights differently from the others (heavier or lighter? Unknown) We have a balance: How can you discover the false coin in 3 weights? AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
20 12 COINS I HAVE NOT A PROGRAM FOR IT! There are 12 coins Exactly one of them is false The false one weights differently from the others (heavier or lighter? Unknown) We have a balance: How can you discover the false coin in 3 weights? AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
21 SMULLYAN AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
22 SMULLYAN AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
23 SMULLYAN AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
24 SMULLYAN AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
25 SMULLYAN AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
26 SMULLYAN AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
27 SMULLYAN AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
28 A NGRY B IRDS AGOSTINO D OVIER (CLPLAB) AUTOMATED REASONING U DINE, D ECEMBER / 24
29 ANGRY BIRDS AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
30 ASP solving (in short) AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
31 A BSTRACT ASP SOLVING Let us see an abstract description of the ASP solver proposed by Yuliya Lierler (Univ. Nebraska at Omaha) Guess who is who in the picture... AGOSTINO D OVIER (CLPLAB) AUTOMATED REASONING U DINE, D ECEMBER / 24
32 SMODELS: ABSTRACT VIEW AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
33 SMODELS: ABSTRACT VIEW AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
34 SMODELS: ABSTRACT VIEW AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
35 CLASP (AND Input Initial Propagation LEVEL=1 Fail Y Violation? N NoGoodCheckandPropagate Fail Y LEVEL=1 Y Violation N TOTAL Y Return A N N Selection Conflict Analysis Update A; Increment LEVEL Update ; Update A; Update LEVEL The key of CLASP efficiency is conflict analysis and nogood learning AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, DECEMBER / 24
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