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26
Representing Transition Systems by Logic Programs
, 1999
"... This paper continues the line of research on representing actions, on the automation of commonsense reasoning and on planning that deals with causal theories and with action language C. We show here that many of the ideas developed in that work can be formulated in terms of logic programs under th ..."
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Cited by 48 (6 self)
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This paper continues the line of research on representing actions, on the automation of commonsense reasoning and on planning that deals with causal theories and with action language C. We show here that many of the ideas developed in that work can be formulated in terms of logic programs under the answer set semantics, without mentioning causal theories. The translations from C into logic programming that we investigate serve as a basis for the use of systems for computing answer sets to reason about action domains described in C and to generate plans in such domains.
Missionaries and Cannibals in the Causal Calculator
"... A knowledge representation formalism... ..."
Representing the Zoo World and the Traffic World in the language of the Causal Calculator
 Artificial Intelligence
, 2004
"... The work described in this report is motivated by the desire to test the expressive possibilities of action language C+. The Causal Calculator (CCalc) is a system that answers queries about action domains described in a fragment of that language. The Zoo World and the Traffic World have been propose ..."
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Cited by 27 (10 self)
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The work described in this report is motivated by the desire to test the expressive possibilities of action language C+. The Causal Calculator (CCalc) is a system that answers queries about action domains described in a fragment of that language. The Zoo World and the Traffic World have been proposed by Erik Sandewall in his Logic Modelling Workshop  an environment for communicating axiomatizations of action domains of nontrivial size. The Zoo World consists of several cages and the exterior, gates between them, and animals of several species, including humans. Actions in this domain include moving within and between cages, opening and closing gates, and mounting and riding animals. The Traffic World includes vehicles moving continuously between road crossings subject to a number of restrictions, such as speed limits and keeping a fixed safety distance away from other vehicles on the road. We show how to represent the two domains in the input language of CCalc, and how to use CCalc to test these representations.
ERES: Reasoning about Actions, Events and Observations
 in LPNMR’01
, 2001
"... The language E for reasoning about actions and change can be translated into an argumentation framework. In this paper, we extend this translation of the basic language and show how it can, together with methods from abduction, form the basis for a principled implementation of E . The extension ..."
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Cited by 16 (5 self)
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The language E for reasoning about actions and change can be translated into an argumentation framework. In this paper, we extend this translation of the basic language and show how it can, together with methods from abduction, form the basis for a principled implementation of E . The extension we have considered concerns the addition of new type of sentences in the language as well as allowing theories where the narrative of events given is incomplete. A system, called ERES, is developed that can support directly a variety of modes of common sense reasoning such as: default persistence in credulous or skeptical form, assimilation of observations and their diagnosis possibly under incomplete information, as well as combinations of these. Application problems that require these modes of reasoning can then be addressed in a natural way directly from their highlevel specification that the language E can provide. To improve the efficiency of the system we have considered, together with a notion of relevancy of constrains, its interface with a SAT solver within the process of validating the time universal constrains imposed by ramification statements. 1
Transformations of logic programs related to causality and planning
 In Logic Programming and Nonmonotonic Reasoning: Proc. Fifth Int'l Conf. (Lecture
, 1999
"... Abstract. We prove two properties of logic programs under the answer set semantics that may be useful in connection with applications of logic programming to representing causality and to planning. One theorem is about the use of disjunctive rules to express that an atom is exogenous. The other prov ..."
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Cited by 13 (6 self)
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Abstract. We prove two properties of logic programs under the answer set semantics that may be useful in connection with applications of logic programming to representing causality and to planning. One theorem is about the use of disjunctive rules to express that an atom is exogenous. The other provides an alternative way of expressing that a plan does not include concurrently executed actions. 1 Introduction In this note we prove two properties of logic programs under the answer set semantics [3] that may be useful in connection with applications of logic programming to representing causality and to planning. According to the first of the two theorems, replacing a disjunctive rule of the form
CPlogic: A Language of Causal Probabilistic Events and Its Relation to Logic Programming
"... We examine the relation between constructive processes and the concept of causality. We observe that causality has an inherent dynamic aspect, i.e., that, in essence, causal information concerns the evolution of a domain over time. Motivated by this observation, we construct a new representation lan ..."
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Cited by 11 (0 self)
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We examine the relation between constructive processes and the concept of causality. We observe that causality has an inherent dynamic aspect, i.e., that, in essence, causal information concerns the evolution of a domain over time. Motivated by this observation, we construct a new representation language for causal knowledge, whose semantics is defined explicitly in terms of constructive processes. This is done in a probabilistic context, where the basic steps that make up the process are allowed to have nondeterministic effects. We then show that a theory in this language defines a unique probability distribution over the possible outcomes of such a process. This result offers an appealing explanation for the usefulness of causal information and links our explicitly dynamic approach to more static causal probabilistic modeling languages, such as Bayesian networks. We also show that this language, which we have constructed to be a natural formalization of a certain kind of causal statements, is closely related to logic programming. This result demonstrates that, under an appropriate formal semantics, a rule of a normal, a disjunctive or a certain kind of probabilistic logic program can be interpreted as a description of a causal event.
Representing Causal Information about a Probabilistic Process
"... Abstract. We study causal information about probabilistic processes, i.e., information about why events occur. A language is developed in which such information can be formally represented and we investigate when this suffices to uniquely characterize the probability distribution that results from s ..."
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Cited by 9 (3 self)
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Abstract. We study causal information about probabilistic processes, i.e., information about why events occur. A language is developed in which such information can be formally represented and we investigate when this suffices to uniquely characterize the probability distribution that results from such a process. We examine both detailed representations of temporal aspects and representations in which time is implicit. In this last case, our logic turns into a more finegrained version of Pearl’s approach to causality. We relate our logic to certain probabilistic logic programming languages, which leads to a clearer view on the knowledge representation properties of these language. We show that our logic induces a semantics for disjunctive logic programs, in which these represent nondeterministic processes. We show that logic programs under the wellfounded semantics can be seen as a language of deterministic causality, which we relate to McCain & Turner’s causal theories. 1
Representing the language of the Causal Calculator in Answer Set Programming
 In Technical Communications of the 27th International Conference on Logic Programming (ICLP
, 2011
"... Action language C+, a formalism based on nonmonotonic causal logic, was designed for describing properties of actions. The definite fragment of C+ was implemented in system the Causal Calculator (CCalc), based on a reduction of nonmonotonic causal logic to propositional logic. On the other hand, in ..."
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Cited by 8 (5 self)
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Action language C+, a formalism based on nonmonotonic causal logic, was designed for describing properties of actions. The definite fragment of C+ was implemented in system the Causal Calculator (CCalc), based on a reduction of nonmonotonic causal logic to propositional logic. On the other hand, in this paper, we represent the language of CCalc in answer set programming (ASP), by translating nonmonotonic causal logic into formulas under the stable model semantics. We design a standard library which describes the constructs of the input language of CCalc in terms of ASP, allowing a simple modular method to represent CCalc input programs in the language of ASP. Using the combination of system f2lp and answer set solvers, our prototype implementation of this approach, which we call Cplus2ASP, achieves functionality close to CCalc while taking advantage of answer set solvers to yield efficient computation that is orders of magnitude faster than CCalc on several benchmark examples.
Representing Synonymity in Causal Logic and in Logic Programming
"... We investigate the relationship between rules representing synonymity in nonmonotonic causal logic and in answer set programming. This question is of interest in connection with current work on modular languages for describing actions. ..."
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Cited by 7 (7 self)
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We investigate the relationship between rules representing synonymity in nonmonotonic causal logic and in answer set programming. This question is of interest in connection with current work on modular languages for describing actions.
Representing FirstOrder Causal Theories by Logic Programs
"... Nonmonotonic causal logic, introduced by Norman McCain and Hudson Turner, became a basis for the semantics of several expressive action languages. McCain’s embedding of definite propositional causal theories into logic programming paved the way to the use of answer set solvers for answering queries ..."
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Cited by 6 (6 self)
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Nonmonotonic causal logic, introduced by Norman McCain and Hudson Turner, became a basis for the semantics of several expressive action languages. McCain’s embedding of definite propositional causal theories into logic programming paved the way to the use of answer set solvers for answering queries about actions described in such languages. In this paper we extend this embedding to nondefinite theories and to firstorder causal logic.