This paper makes use of high-level action languages to investigate aspects of causality that are central to ethical reasoning. We identify properties that causal relations assume and that determine how, as well as to ...
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ISBN:
(纸本)9781450356497
This paper makes use of high-level action languages to investigate aspects of causality that are central to ethical reasoning. We identify properties that causal relations assume and that determine how, as well as to what extent, we may ascribe ethical responsibility on their basis. The paper is structured in three parts. First, we present an extension of the Event Calculus that enables the agent to generate plans of actions, with the particularity that they integrate both actions and omissions. Second, we present an account of event-based causality that is grounded in the architecture of event preconditions and effects, and that distinguishes four types of causal relations contingent on the nature of the entities that compose them. Namely, it discriminates actions and omissions from automatic events, and produced outcomes from avoided ones. Third, we examine notions of scenario-based causality whose role it is to scrutinise and buttress the causal relations previously identified. Inquiring into the other possible versions of modelled scenarios, we account for simple counter-factual validity ("Had I not acted so, would this outcome still be true?"), criticality ("Could anything else have led to this outcome?"), extrinsic necessity ("Had I not produced it, was this outcome even avoidable?"), and elicited necessity ("Have I made this outcome unavoidable?"). The model is implemented in answer set programming.
answer set programming (ASP) is a purely-declarative logic programming language allowing for disjunction and nonmonotonic negation. The evaluation of ASP programs is traditionally carried out in two steps. In the firs...
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ISBN:
(纸本)9781605588599
answer set programming (ASP) is a purely-declarative logic programming language allowing for disjunction and nonmonotonic negation. The evaluation of ASP programs is traditionally carried out in two steps. In the first step an input program 2 undergoes the so-called instantiation (or grounding) process, which produces a program P' semantically equivalent to 7, but not containing any variable;in turn, P' is evaluated by using a backtracking search algorithm in the second step. It is well-known that instantiation is important for the efficiency of the whole evaluation, might becomes a bottleneck in common situations, and is particularly crucial when huge input data has to be dealt with. In the last few years, several instantiators have been proposed but none of them is able to take advantage from the latest hardware offering SMP (Symmetric Multi Processing) also for entry-level systems and PCs. This paper presents a new parallel version of the instantiator of DLV which is able to exploit the processing power offered by multi-core/multi-processor SMP machines. In particular, the employed parallelization methods, load-balancing and granularity control heuristics, tailored for parallel ASP instantiation process are described. The results of an experimental analysis are also presented, which confirm that multi-core/multi-processor technology can be efficiently exploited for ASP instantiation.
In this paper we take on Stuart C. Shapiro's challenge of solving the Jobs Puzzle automatically and do this via controlled natural language processing. Instead of encoding the puzzle in a formal language that migh...
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In this paper we take on Stuart C. Shapiro's challenge of solving the Jobs Puzzle automatically and do this via controlled natural language processing. Instead of encoding the puzzle in a formal language that might be difficult to use and understand, we employ a controlled natural language as a high-level specification language that adheres closely to the original notation of the puzzle and allows us to reconstruct the puzzle in a machine-processable way and add missing and implicit information to the problem description. We show how the resulting specification can be translated into an answerset program and be processed by a state-of-the-art answerset solver to find the solutions to the puzzle.
This paper applies the logic-based formalism of answer set programming (ASP) to the modelling of competition, inhibition and cycles in biochemical networks. In particular, it introduces a generic framework that unifie...
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ISBN:
(纸本)9781479943258
This paper applies the logic-based formalism of answer set programming (ASP) to the modelling of competition, inhibition and cycles in biochemical networks. In particular, it introduces a generic framework that unifies the competitive and inhibitory mechanisms proposed in the literature along with their complementary approaches to reasoning about loops. We show how the nonmonotonic effects of competition and inhibition can be naturally encoded in the formalism of ASP and that the different ways of handling loops correspond to the computation of stable and supported models. We also show that inhibitory models are currently more general than competitive models and we argue that that both interpretations of loops are justified in some applications.
We describe eclingo, a solver for epistemic logic programs under Gelfond 1991 semantics built upon the answer set programming system clingo. The input language of eclingo uses the syntax extension capabilities of clin...
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We describe eclingo, a solver for epistemic logic programs under Gelfond 1991 semantics built upon the answer set programming system clingo. The input language of eclingo uses the syntax extension capabilities of clingo to define subjective literals that, as usual in epistemic logic programs, allow for checking the truth of a regular literal in all or in some of the answersets of a program. The eclingo solving process follows a guess and check strategy. It first generates potential truth values for subjective literals and, in a second step, it checks the obtained result with respect to the cautious and brave consequences of the program. This process is implemented using the multi-shot functionalities of clingo. We have also implemented some optimisations, aiming at reducing the search space and, therefore, increasing eclingo 's efficiency in some scenarios. Finally, we compare the efficiency of eclingo with two state-of-the-art solvers for epistemic logic programs on a pair of benchmark scenarios and show that eclingo generally outperforms their obtained results.
answer set programming (ASP) is pro- posed as a compact and versatile approach to circuit analysis. By the example of upsets in registers we demonstrate how to perform reliability analysis in less than 200 lines of co...
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ISBN:
(纸本)9781728176703
answer set programming (ASP) is pro- posed as a compact and versatile approach to circuit analysis. By the example of upsets in registers we demonstrate how to perform reliability analysis in less than 200 lines of code. By an efficient problem encoding we achieve an input data format similar to a Verilog netlist so that extensive preprocessing is avoided. No development of algorithms is required as the analysis relies on elaborate and highly optimized ASP solvers. Exemplary results for a wide range of circuits are presented and potential optimizations are pointed out.
An approach to the revision of logic programs under the answerset semantics is presented. For programs P and Q, the goal is to determine the answersets that correspond to the revision of P by Q, denoted P * Q. A fun...
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An approach to the revision of logic programs under the answerset semantics is presented. For programs P and Q, the goal is to determine the answersets that correspond to the revision of P by Q, denoted P * Q. A fundamental principle of classical (AGM) revision, and the one that guides the approach here, is the success postulate. In AGM revision, this stipulates that alpha is an element of K * alpha. By analogy with the success postulate, for programs P and Q, this means that the answersets of Q will in some sense be contained in those of P * Q. The essential idea is that for P * Q, a three-valued answerset for Q, consisting of positive and negative literals, is first determined. The positive literals constitute a regular answerset, while the negated literals make up a minimal set of naf literals required to produce the answerset from Q. These literals are propagated to the program P, along with those rules of Q that are not decided by these literals. The approach differs from work in update logic programs in two main respects. First, we ensure that the revising logic program has higher priority, and so we satisfy the success postulate;second, for the preference implicit in a revision P * Q, the program Q as a whole takes precedence over P, unlike update logic programs, since answersets of Q are propagated to P. We show that a core group of the AGM postulates are satisfied, as are the postulates that have been proposed for update logic programs.
This paper introduces the agent platform HumanSim, a combination of the BDI-paradigm and answer set programming (ASP), to simulate entities in three-dimensional virtual environments. We show how ASP can be used to (i)...
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ISBN:
(纸本)9783319458892;9783319458885
This paper introduces the agent platform HumanSim, a combination of the BDI-paradigm and answer set programming (ASP), to simulate entities in three-dimensional virtual environments. We show how ASP can be used to (i) annotate a virtual three-dimensional world and (ii) to model the goal selection behavior of a BDI agent. Using this approach it is possible to model the agent domain and its behavior - reactive or foresighted - with ASP. To demonstrate the practical use of HumanSim, we present a three-dimensional planning and simulation application, in which worker agents are driven by HumanSim in the shop floor domain. Furthermore, we show the results of an evaluation of HumanSim in the former mentioned simulation application.
The need for integration of ontologies with nonmonotonic rules has been gaining importance in a number of areas, such as the Semantic Web. A number of researchers addressed this problem by proposing a unified semantic...
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The need for integration of ontologies with nonmonotonic rules has been gaining importance in a number of areas, such as the Semantic Web. A number of researchers addressed this problem by proposing a unified semantics for hybrid knowledge bases composed of both an ontology (expressed in a fragment of first-order logic) and nonmonotonic rules. These semantics have matured over the years, but only provide solutions for the static case when knowledge does not need to evolve. In this paper we take a first step towards addressing the dynamics of hybrid knowledge bases. We focus on knowledge updates and, considering the state of the art of belief update, ontology update and rule update, we show that current solutions are only partial and difficult to combine. Then we extend the existing work on ABox updates with rules, provide a semantics for such evolving hybrid knowledge bases and study its basic properties. To the best of our knowledge, this is the first time that an update operator is proposed for hybrid knowledge bases.
Inferring a LTLf formula from a set of example traces, also known as passive learning, is a challenging task for model-based techniques. Despite the combinatorial nature of the problem, current state-of-the-art soluti...
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ISBN:
(纸本)9783031492983;9783031492990
Inferring a LTLf formula from a set of example traces, also known as passive learning, is a challenging task for model-based techniques. Despite the combinatorial nature of the problem, current state-of-the-art solutions are based on exhaustive search. They use an example at the time to discard a single candidate formula at the time, instead of exploiting the full set of examples to prune the search space. This hinders their applicability when examples involve many atomic propositions or when the target formula is not small. This short paper proposes the first ILP-based approach for learning LTLf formula from a set of example traces, using a learning from answersets system called ILASP. It compares it to both pure SAT-based techniques and the exhaustive search method. Preliminary experimental results show that our approach improves on previous SAT-based techniques and that has the potential to overcome the limitation of an exhaustive search by optimizing over the full set of examples. Further research directions for the ILP-based LTLf passive learning problem are also discussed.
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