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

This Festschrift is released in honor of Gerhard Brewka at the social gathering of his sixtieth birthday and comprises articles from fields reflecting the breadth of Gerd's paintings. The 24 clinical papers integrated within the publication are written by way of shut associates and co-workers and canopy themes resembling activities and brokers, Nonmonotonic and Human Reasoning, personal tastes and Argumentation.

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**Sample text**

Step(1)} (1) It is straightforward to verify that the action move(1, 3, 2, 3) is possible in this state: After adding each of the facts in true|s0 , the unique stable model of the resulting program includes true(cell (2, 3, empty)), true(cell (1, 3, 6)) and succ(1, 2), hence also legal(move(1, 3, 2, 3)) according to clause 19. From Definition 2 and the clauses 24–32 it follows that δ(move(1, 3, 2, 3), s0) = {cell (1, 1, 9), . . , cell (1, 3, empty), cell (2, 3, 6), . . , step(2)} Given two state transition systems, the standard deﬁnition of a simulation requires that one matches all actions in the other.

In what follows, we represent partial assignments either by At , Af or At , Au by leaving the respective default value implicit. 4 That is, input atoms are externals that are not overridden by rules in P . Given a partial assignment I t , I u over I, we define P I t ,I u = P ∪ ({a ← | a ∈ I t } ∪ {{a} ← | a ∈ I u }) to capture the extension of P with respect to an (external) truth assignment to the input I. 5 Then, X is a stable model of a program P with externals E filtered by At , Af , if X is a stable model of P I t ,I u such that At ⊆ X and Af ∩ X = ∅.

15 ,13 ,0 , 1 ) . (10 ,14 ,0 , 1 ) . ( 3 ,15 ,0 , 1 ) . 2 gives the sixteen possible target locations printed on the game’s carton board (cf. Line 3 to 18). Each robot has four possible target locations, expressed by the ternary predicate target. Such a target is put in place via the unary predicate goal that associates a number with each location. The external declaration in Line 1 paves the way for fixing the target location from outside the solving process. For instance, setting goal(13) to true makes position (15,13) a target location for the yellow robot.