Download PDF by Thomas Eiter, Hannes Strass, Miroslaw Truszczyński, Stefan: Advances in Knowledge Representation, Logic Programming, and

By Thomas Eiter, Hannes Strass, Miroslaw Truszczyński, Stefan Woltran

ISBN-10: 3319147250

ISBN-13: 9783319147253

ISBN-10: 3319147269

ISBN-13: 9783319147260

This Festschrift is released in honor of Gerhard Brewka at the get together of his sixtieth birthday and includes articles from fields reflecting the breadth of Gerd's paintings. The 24 clinical papers incorporated within the ebook are written by way of shut associates and co-workers and canopy themes similar to activities and brokers, Nonmonotonic and Human Reasoning, personal tastes and Argumentation.

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0). ,0). barrier barrier barrier barrier barrier barrier ( 9 , 7 ,0 , (11 , 7 ,0 , (14 , 7 ,0 , (16 , 9 ,0 , ( 2 ,10 ,0 , ( 5 ,10 ,0 , 1). 1). 1). 1). 1). 1). The encodings in [9] rely on the input language of clingo 3 [16,17]. 3. 24 9 10 11 12 13 14 15 16 17 18 19 M. Gebser et al. barrier barrier barrier barrier barrier barrier barrier barrier barrier barrier barrier ( 7 , 4 , 1 ,0). ( 3 , 7 , 1 ,0). (14 , 7 , 1 ,0 ). ( 7 , 8 , 1 ,0). ( 1 0 , 8 , − 1 , 0 ). (11 , 8 , 1 ,0 ). ( 7 , 9 , 1 ,0). ( 1 0 , 9 , − 1 , 0 ).

3 allows us to derive pos(yellow,15,13,0) and makes it the new starting position of the yellow robot, as shown on the left hand side of Figure 2. Line 36–44 show the code for configuring the player. They set the search horizon, the encodings to solve with, and the initial positions in form of gringo terms. Furthermore, we fix a sequence of goals in Line 42–44. In a more realistic setting, either some user interaction or a random sequence might be generated to emulate arbitrary draws. 8. Multi-shot solving with clingo 4’s Python module 1 2 3 4 $ p y t h o n r i c o c h e t .

Create() : → ∅, ∅, ∅ – add (R) : Q, P, I → Q ∪ R, P, I where R is a (non-ground) logic program – ground : Q, P1 , I1 → ∅, P2 , I2 where6 • (P, E) = grdP1 ,I1 (Q) • P2 = P1 ∪ P • I2 = (I1 ∪ E) \ H(P2 ) ◦ I2t = {a ∈ I2 | I1 (a) = t } ◦ I2u = {a ∈ I2 | I1 (a) = u} – assignExternal (a, t) : Q, P, I1 → Q, P, I2 where • I2 = I1 ◦ I2t = I1t ∪ {a} if a ∈ I1 , and I2t = I1t otherwise ◦ I2u = I1u \ {a} assignExternal (a, u) : Q, P, I1 → Q, P, I2 where • I2 = I1 ◦ I2t = I1t \ {a} ◦ I2u = I1u ∪ {a} if a ∈ I1 , and I2u = I1u otherwise assignExternal (a, f ) : Q, P, I1 → Q, P, I2 where • I2 = I1 ◦ I2t = I1t \ {a} ◦ I2u = I1u \ {a} – releaseExternal (a) : Q, P1 , I1 → Q, P2 , I2 where • P2 = P1 ∪ {a ← a, ∼a} if a ∈ I1 , and P2 = P1 otherwise • I2 = I1 \ {a} ◦ I2t = I1t \ {a} ◦ I2u = I1u \ {a} – solve( At , Af ) : Q, P, I → Q, P, I outputs the set XP,I defined as {X | X is a stable model of P I t ,I u such that At ⊆ X and Af ∩ X = ∅} (4) For simplicity, we dropped the condition ‘I2f = I2 \ (I2t ∪ I2u )’ from all transitions of I1 to I2 because undefined input atoms are regarded to be false.

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Advances in Knowledge Representation, Logic Programming, and Abstract Argumentation: Essays Dedicated to Gerhard Brewka on the Occasion of His 60th Birthday by Thomas Eiter, Hannes Strass, Miroslaw Truszczyński, Stefan Woltran


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