Knowledge representation with logic programs

Brewka, Gerhard; Dix, Jürgen

doi:10.1007/bfb0054788

Cited by 8 publications

(7 citation statements)

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“…The main ideas introduced in this paper are (1) to introduce a new kind of Petri net, the simple logic Petri net, (2) to use these nets for specifying (AgentSpeak-) agents, and (3) to transform these nets into logic programs and use ASP engines [1,5,7,8] for solving the model-checking task-the detection of deadlocks in SLPN's.…”

Section: Mas) Classical Techniques Like Simulationmentioning

confidence: 99%

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Model checking multi-agent systems with logic based Petri nets

Behrens

Dix

2007

Ann Math Artif Intell

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We introduce a class of Petri nets, simple logic Petri nets (SLPN), that are based on logical expressions. We show how this type of nets can be efficiently mapped into logic programs with negation: the corresponding answer sets describe interleaved executions of the underlying nets (Theorem 1). The absence of an answer set indicates a deadlock situation. We also show how to correctly model and specify AgentSpeak agents and multi-agent systems with SLPN's (Theorem 2). Both theorems allow us to solve the task of model checking AgentSpeak multi-agent systems by computing answer sets of the obtained logic program with any ASP system.

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Section: Mas) Classical Techniques Like Simulationmentioning

confidence: 99%

“…This corresponds to a deadlock. When no transitions are activated (in step 5), then the constraint ← ¬ f ires(t1, 5), ¬ f ires(t2, 5) can not be satisfied.…”

Section: Asp Representationmentioning

confidence: 99%

Model checking multi-agent systems with logic based Petri nets

Behrens

Dix

2007

Ann Math Artif Intell

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“…Nonmonotonic logic programs extend classical Horn logic programs by the introduction of negation as failure, and provide a powerful tool for representing and reasoning with incomplete information [3,7]. As nonmonotonic logic programs are considered a subclass of default theories, techniques of ordering default theories are directly applied to the problem of ordering logic programs.…”

Section: • Comparison Of Different Default Theoriesmentioning

confidence: 99%

“…Intuitively, (F ) ∈ {t, f} means that F or ¬F is a definite conclusion from W. When (F ) = for some formula F, (G) = for any formula G. This is because in this case W is inconsistent and entails every formula. 7 On the other hand, when (F ) ∈ {dts, dfs} (resp., (F ) ∈ {dtc, dfc}), F or ¬F is a default conclusion inferred skeptically (resp., credulously) from . When (F ) = * , a formula F belongs to some extension and its negation ¬F belongs to another extension.…”

Section: Multi-valued Interpretation Of Default Theoriesmentioning

confidence: 99%

“…Program transformations considered here are: unfold/fold (UNFOLD/FOLD), elimination of tautologies (TAUT), positive/negative reduction (RED + /RED − ), elimination of nonminimal rules (NONMIN), and elimination of contradictions (CONTRA). These are basic and representative transformations appearing in the literature [7,26]. It is known that the above program transformations all preserve the answer sets of an ELP [1,7].…”

Section: Transformational Propertiesmentioning

confidence: 99%

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Ordering default theories and nonmonotonic logic programs

Sakama

2005

Theoretical Computer Science

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First-order theories are ordered under logical entailment based on the amount of information derived from theories. In default logic, on the other hand, a theory contains default information as well as definite information. To order default theories, distinguishing different sorts of information is necessary to assess the information content of a default theory. For this purpose, we first introduce a multi-valued interpretation of default theories using a ten-valued bilattice. It distinguishes between definite and credulous/skeptical default information derived from a theory, and is used for ordering default theories based on their information contents. We then apply the technique to order nonmonotonic logic programs under the answer set semantics. The results of this paper provide a method for comparing default theories or nonmonotonic logic programs in a manner different from the conventional extension/model-based viewpoint. Moreover, they have important application to induction from nonmonotonic theories.

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