C. Baral, A. Gabaldon, and A. Provetti. Formalizing narratives using nested circumscription. Artificial Intelligence, 104(1-2):107--164, 1998.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....problems. Since then, NATs have been used by a number of authors and are gaining popularity as a circumscriptive knowledge representation tool. For example, NATs have been used in reasoning about actions [25, 24, 31, 32, 48] for handling the qualification problem [39] formalizing narratives [3], expressing function value minimization [2] information filtering [1] describing action selection in planning [47] and in spatial reasoning [43] As another simple example for combining circumscriptions, imagine the task to diagnose a malfunctioning artifact which is composed of modular ....

.... with that of quantified Boolean formulas (QBFs) makes fast prototype implementations possible by translating them into a QBF and then using one of the several available solvers, e.g. 44] This approach could be used also for implementing meaningful fragments of NATs, such as the one in [3], although this might be inefficient, like using a first order theorem prover for propositional logic. Given that QBFs can be polynomially encoded into NATs, we can show that nested circumscription is more succinct than plain (unnested) circumscription, i.e. by nesting CIRC operators (or NATs) ....

C. Baral, A. Gabaldon, and A. Provetti. Formalizing narratives using nested circumscription. Artificial Intelligence, 104(1-2):107--164, 1998.

.... as Programs Ray Reiter Department of Computer Science University of Toronto Toronto, Canada M5S 3G4 reiter cs.toronto.edu Abstract Representing narratives, and reasoning about them, has been a prominent theme in logical formalisms for dynamical systems (e.g. [9, 5, 2]) However, the existing literature provides a rather limited concept of what a narrative is; the examples all concern linear action sequences, sometimes including incomplete information about action occurrence times. The point of departure of this paper is the observation that narratives ....

C. Baral, A. Gabaldon, and A. Provetti. Formalizing narratives using nested circumscription. Artificial Intelligence, 104:107--164, 1998.

....i.e. Circ(T 1 ) Circ(T 2 ) 1 . In L Circ , all propositional connectives are allowed. As for the latter extension, the original idea of nested abnormality theories (NATs) has been proposed by Lifschitz [1995] and its usefulness for the formalization of narratives has been shown by Baral et al. 1998] . Nesting circumscription is useful for the modularization of a knowledge base. As an example concerning diagnosis of an artifact designed in a modular way, e.g. a car, a piece of knowledge Circ(T 1 ) may model the intended behavior of a subpart, e.g. the engine. Analogously, Circ(T 2 ) may ....

.... with that of quantified Boolean formulas (QBFs) makes fast implementations possible by translating them into a QBF and then using one of the several available solvers, e.g. Rintanen, 1999] This approach could be used also for implementing meaningful fragments of NATs, such as the one in [Baral et al. 1998] , although this might be inefficient, like using a first order theorem prover for propositional logic. Given that QBFs can be polynomially encoded into NATs, we can show (in the full paper) that nested circumscription is more succinct than plain (unnested) circumscription, i.e. by nesting Circ ....

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C. Baral, A. Gabaldon, and A. Provetti. Formalizing narratives using nested circumscription. Artificial Intelligence, 104(1-2):107--164, 1998.

....value minimizing a function consists in choosing those models where the value of the function is minimal relative to an ordering on its range. We first considered minimizing functions when trying to translate specifications in the action description language L into circumscriptive theories [1]. There, we introduced a function Sit map that maps situations into sequences of actions; these sequences, intuitively, represent the history of the domain up to the situation itself. Assuming that no action has happened unless so suggested by the observations, corresponds to requiring each ....

....: Cm are varying. 4 Applying value minimization to reasoning about actions In this section, we discuss a recent application of, and motivation for, value minimization in a full scale knowledge representation problem, namely, reasoning about actual and hypothetical occurrences of actions. In [1] we introduced a sound and complete formalization of narratives for domains specified in the high level action description language L [2] In the development of this formalization of narratives, we were faced with the problem of minimizing the value of a particular term: Sit map(SN ) that mapped ....

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C. Baral, A. Gabaldon and A. Provetti. Formalizing Narratives using Nested Circumscription. In Proc. of 14th AAAI National Conference on Artificial Intelligence (1996) 652--657. 28

....actions and forms the basis of classical planning. But in its original form it does not allow narratives; the only actual observations that can be expressed in it are about values of fluents in the initial situation. 1.1. Allowing narratives with hypothetical reasoning Recently, researchers [5,19,33,35,36,39] have realized the importance of having a formalism that captures both narratives and hypothetical reasoning about effects of actions. Such a formalism is necessary to formulate planning and execution of actions of an agent in a dynamic environment, where exogenous actions may occur. The agent has ....

C. Baral, A. Gabaldon, A. Provetti, Formalizing narratives using nested circumscription, in: Proc. 14th National Conference on Artificial Intelligence (AAAI-96), Portland, OR, 1996, pp. 652--657.

....Texas action group where the idea of filtering is used are: The notion of nested circumscription in [Lif95] is a generalization of the notion of filtering where multiple levels of filtering can be expressed. Nested circumscription is used in his works in [KL94] and also by others in [BGP98b,BGP98a] for formalizing reasoning about actions. Lifschitz in [Lif99] points out that writing observations as constraints as opposed to facts that are directly added to the theory, as one of the three principles followed by McCain and Turner in their formulation [MT97,Tur97] using Reiter s ....

.... (or false as the consequent) and in case of logic programs constraints are represented using rules with empty head (or false in the head) Baral and Gelfond also represent observations as constraints in their logic programming formulation in [BG97] and Baral, Gabaldon and Provetti in [BGP98b,BGP98a] use nested circumscription to formulate narratives. 1.2 Relating filtering and abductive reasoning: Motivations Besides the fact that both filtering and abductive reasoning are used for assimilating observations, our motivations to study the relationship between the two are as follows: i) ....

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C. Baral, A. Gabaldon, and A. Provetti. Formalizing Narratives using nested circumscription. Artificial Inteligence, 104(1-2):107--164, Sept 1998.

....and a unobservable fluent. We then use this language to define the notion of a conditional plan, and the related notions of diagnostic and repair planning. Finally, in Section 5 we summarize and discuss related work. 2 Specifying narrative in L The propositional language L was developed in [BGP97, BGP98] to specify narratives and to reason with them. In this paper, we will describe the main aspects of the language L by dividing it into three components: a domain description language LD , a language to specify observations LO , and a query language LQ . In Section 4.1, we extend our language ....

....causal laws, describe causal relation between fluents in a world. Propositions of the form (3) called executability conditions, state when actions are not executable. A domain description D is a set of propositions in LD . The main difference between LD and the action description part of L [BGP97, BGP98] is the presence of static causal laws in LD , which are critical for representing the behavior of the device being diagnosed. A domain description given in LD defines a transition function from actions and states to a set of states. Recall, actions may be nondeterministic. Intuitively, given ....

C. Baral, A. Gabaldon, and A. Provetti. Formalizing Narratives using nested circumscription. Artificial Intelligence, 104(1-2):107--164, 1998.

....uent and a unobservable uent. We then use this language to de ne the notion of a conditional plan, and the related notions of diagnostic and repair planning. Finally, in Section 5 we summarize and discuss related work. 2 Specifying narrative in L The propositional language L was developed in [BGP97, BGP98] to specify narratives and to reason with them. In this paper, we will describe the main aspects of the language L by dividing it into three components: a domain description language LD , a language to specify observations LO , and a query language LQ . In Section 4.1, we extend our language ....

....static causal laws, describe causal relation between uents in a world. Propositions of the form (3) called executability conditions, state when actions are not executable. A domain description D is a set of propositions in LD . The main di erence between LD and the action description part of L [BGP97, BGP98] is the presence of static causal laws in LD , which are critical for representing the behavior of the device being diagnosed. A domain description given in LD de nes a transition function from actions and states to a set of states. Recall, actions may be nondeterministic. Intuitively, given an ....

C. Baral, A. Gabaldon, and A. Provetti. Formalizing Narratives using nested circumscription. Articial Intelligence, 104(1-2):107-164, 1998.

....on the assumption that the only information we have is the information about the current state. In real life, in addition to the information about the current state, we often have some information about the previous behavior of the system. To describe such more realistic planning problems, in [1, 2], the language A was extended to a new language L. In this new language, to describe the history of the system, first of all, the current state s N is separated from the initial state s 0 , so we may have statements about what is true at s 0 ( F at s 0 ) and statements about what is true at s N ....

Baral, C., Gabaldon, A., Provetti, A.: Formalizing Narratives Using Nested Circumscription, AI Journal 104 (1998) 107--164.

....description languages concentrated on the former and hence required rather powerful logics such as circumscription, disjunctive or abductive logic programming, etc. In contrast, in this paper we will concentrate on the latter (for sound and complete translation of L 1 into circumscription see [BGP96]) Our translation D of D will be a declarative logic program (under answer set semantics) used together with the inference mechanism incorporated in the standard Prolog interpreter (as implemented, for instance, in Quintus Prolog) It is well known that in general this mechanism is not complete ....

C. Baral, A. Gabaldon, and A. Provetti. Formalizing Narratives using nested circumscription. In Common Sense 96, (http://wwwformal. stanford.edu/tjc/96FCS/Final-papers/), 1996.

.... useful, to general and provenly correct theories [GL93, San92, San94, Rei91, LS91, LS95] that incrementally consider various specification aspects such as: actions with non deterministic effects [Bar95, Pin94, KL94, San93] concurrent actions [LS92, BG93, BG97a] narratives [MS94, PR93, BGP97, BGPml, Kar98] actions with duration [Sho86, San89, San93, San94, MS94, Rei96] natural events [Rei96] ramifications and qualifications due to simple and causal constraints [LR94, KL94, Bar95, Lin97, Thi97, MT95, Lin95, Bar95, GL95, San96, GD96] sensing (or knowledge producing) actions [Moo77, Moo79, ....

C. Baral, A. Gabaldon, and A. Provetti. Formalizing Narratives using nested circumscription. In AAAI 96, pages 652--657, 1996 (Extended version with proofs available at http://cs.utep.edu/chitta/chitta.html).

....the results of different tests ( sensing actions ) Since this additional information is very important in many practical planning problems, it is desirable to include this information into the corresponding AI formalisms. To describe the use of knowledge about the past in planning problems, in [1, 2], the language A was extended to a new language L. In this new language, to describe the history of the system, first of all, the current state s N is separated from the initial state s 0 , so we may have statements about what is true at s 0 ( F at s 0 ) and statements about what is true at s N ....

Baral, C., Gabaldon, A., Provetti, A.: Formalizing Narratives Using Nested Circumscription, AI Journal 104 (1998) 107--164.

....reasoning about actions and forms the basis of classical planning. But in its original form it does not allow narratives; the only actual observations that can be expressed in it are about values of fluents in the initial situation. Recently, researchers [MilSha94,KakMil96,PinRei93,McC95,BarGabPro96a,Pro96] have realized the importance of having a formalism that allows both hypothetical reasoning about effects of actions and narratives. Such a formalism is necessary to formulate planning and execution of actions of an agent in a dynamic environment, where exogenous actions may occur. The ....

Baral C., Gabaldon A. and Provetti A. 1996. Formalizing Narratives using Nested Circumscription. In Proceedings of the 14th National Conference on Artificial Intelligence (AAAI96), pp. 652--657, Portland, Oregon.

.... which were extremely useful, to general and provenly correct theories [GL93,San92,Rei91,LS91,LS95] that incrementally consider various specification aspects such as: actions with non deterministic effects [Bar95,Pin94,KL94] concurrent actions [LS92,BG93,BG97] narratives [MS94,PR93,BGP97,BGP96] actions with duration [MS94,Rei96] natural events [Rei96] ramifications and qualifications due to simple and causal constraints [LR94,KL94,Bar95,Lin97,Thi97,MT95] Lin95,Bar95,GL95] sensing (or knowledge producing) actions [Moo77,Moo79,Moo85,SL93,LTM97,BS97a] etc. Most of the above ....

C. Baral, A. Gabaldon, and A. Provetti. Formalizing Narratives using nested circumscription. In AAAI 96, pages 652--657, 1996.

....of classical planning. But in its original form it does not allow narratives; the only actual observations that can be expressed in it are about values of fluents in the initial situation. 1. 1 Allowing narratives with hypothetical reasoning Recently, researchers [MilSha94,KakMil96,PinRei93,McC95,BarGabPro96a,Pro96] have realized the importance of having a formalism that captures both narratives and hypothetical reasoning about actions effects. Such a formalism is necessary to formulate planning and execution of actions of an agent in a dynamic environment, where exogenous actions may occur. The ....

Baral C., Gabaldon A. and Provetti A. 1996. Formalizing Narratives using Nested Circumscription. In Proceedings of the 14th National Conference on Artificial Intelligence (AAAI'96), pp. 652--657. 76

....may change their values, or mental objects that encode the mental state of the robot agent. For example, loaded is fluent which tells us if the gun is loaded or not. 4 actions with non deterministic effects [Bar95,Pin94,KL94] concurrent actions [LS92,BG93,BG97a] narratives [MS94,PR93,BGP97,BGP96] actions with duration [MS94,Rei96] natural events [Rei96] ramifications and qualifications due to simple and causal constraints [LR94,KL94,Bar95,Lin97,Thi97,MT95] Lin95,Bar95,GL95] sensing (or knowledge producing) actions [SL93,JTM97] etc. Most of the above formalizations define an ....

C. Baral, A. Gabaldon, and A. Provetti. Formalizing Narratives using nested circumscription. In AAAI 96, 1996.

....can itself be part of another circumscription. The NAT method seems very promising for our long term task of modeling reasoning about change. We first considered minimizing functions when trying to translate specifications in the action description language L into circumscriptive theories [BGabP96]. There, we introduced a function Sit map that maps situations into sequences of actions; these sequences, intuitively, represent the history of the domain up to the situation itself. Assuming that no action has happened unless so suggested by the observations correspond to requiring each sequence ....

....of Section 2 below, makes conventional Linear programming , constraint programming and scheduling not immediately viable. In the paper we give an explicit (syntactic) and a model theoretic definition of value minimization of functions, in Sections 3 and 4; generalize the formulation in [BGabP96], and show how value minimization of functions can be accomplished by NAT predicate minimization in Section 7; define many functions minimization, with or without priorities among them, and the corresponding NAT structure, and define value minimization of predicates that actually encode ....

[Article contains additional citation context not shown here]

C. Baral, A. Gabaldon and A. Provetti. Formalizing Narratives using Nested Circumscription. In Proc. of 14th AAAI National Conference on Artificial Intelligence (1996) 652--657. Also in the Working notes of the 3rd symposium Logical Formalizations of Common-sense Reasoning, 15--24.

....situation s 0 , in all models of the theory. We will now argue that given a complete set of Holds literals at the situation s, for any action A, their is a unique (and complete) set of Holds literals at the situation Res(A; s) in all models of the theory. A detailed proof of this is given in [BGPml]. The NAT block defining Causes ( Gamma) guarantees that given a complete set of Holds literals at a situation s, we have a unique (and complete) set of Causes ( Gamma) literals at the situation s, w.r.t. any action A, and any fluent F . Because of our restrictions on domain ....

C. Baral, A. Gabaldon, and A. Provetti. Formalizing Narratives using nested circumscription. In AAAI 96, pages 652--657, 1996 (Extended version with proofs available at http://cs.utep.edu/chitta/chitta.html).

No context found.

C. Baral, A.Gabaldon and A. Provetti. Formalizing Narratives using Nested Circumscription. In Proc. of 14th AAAI National Conference on Artificial Intelligence (1996) 652--657. Also in the Working notes of the 3rd symposium Logical Formalizations of Commonsense Reasoning, 15--24.

....is detailed in our earlier work [BS96, BS97a, BS97b] In this theory we are concerned with the control of one agent in a dynamic environment, where exogenous events beyond the control of our agent may occur. Our agent has an action theory (such as a theory in the language [GL93, KL94, San94, BGP96] where actions and their effects are specified together with constraints and causal rules about the environment. Our theory contains a formulation of correctness of a control module a control module is a collection of control rules of the form if p 1 ; p n then a, where p i s are ....

C. Baral, A. Gabaldon, and A. Provetti. Formalizing Narratives using nested circumscription. In AAAI 96, 1996.

No context found.

C. Baral, A. Gabaldon, and A. Provetti. Formalizing Narratives using nested circumscription. In AAAI 96 (to appear), 1996.

....description languages concentrated on the former and hence required rather powerful logics such as circumscription, disjunctive or abductive logic programming, etc. In contrast, 21 in this paper we will concentrate on the latter (for sound and complete translation of L 1 into circumscription see [BGP96]) Our translation Pi D of D will be a declarative logic program (under answer set semantics) used together with the inference mechanism incorporated in the standard Prolog interpreter (as implemented, for instance, in Quintus Prolog) It is well known that in general this mechanism is not ....

C. Baral, A. Gabaldon, and A. Provetti. Formalizing Narratives using nested circumscription. Proc. of the 14th AAAI National Conference on Artificial Intelligence, 1996. An earlier version is in the Working notes of the third symposium Logical Formalizations of Commonsense Reasoning, pages 15--24.

....is detailed in our earlier work [BS96, BS97a, BS97b] In this theory we are concerned with the control of one agent in a dynamic environment, where exogenous events beyond the control of our agent may occur. Our agent has an action theory (such as a theory in the language [GL93, KL94, San94, BGP96] where actions and their effects are specified together with constraints and causal rules about the environment. 3 To focus on the main point we have simplified the real requirement a little bit. Our theory contains a formulation of correctness of a control module 4 with respect to an ....

C. Baral, A. Gabaldon, and A. Provetti. Formalizing Narratives using nested circumscription. In AAAI 96, pages 652--657, 1996.

....a unique salary and a unique name. Hence, we can intuitively view the above minimization as minimizing a function F sal that maps employee ids into salaries. Notice, however, that we are not minimizing the extent of the function 1 , rather we are minimizing the value of the function. Recently in [Baral et al. 1996a] we have discussed the relationship between specifications in the action description language L [Baral et al. 1996b] and circumscriptive theories. There we were faced with the minimization of a particular term, sit map(SN ) that mapped the current situation symbol SN onto a sequence of ....

....that maps employee ids into salaries. Notice, however, that we are not minimizing the extent of the function 1 , rather we are minimizing the value of the function. Recently in [Baral et al. 1996a] we have discussed the relationship between specifications in the action description language L [Baral et al. 1996b] and circumscriptive theories. There we were faced with the minimization of a particular term, sit map(SN ) that mapped the current situation symbol SN onto a sequence of actions, understood as the history of the 1 To stay close to the usual circumscription terminology, we use extent of a ....

[Article contains additional citation context not shown here]

Baral C., Gabaldon A., and Provetti A., 1996. Formalizing Narratives using Nested Circumscription. In Proc. of 14th AAAI National Conference on Artificial Intelligence, pages 652--657. Also in the Working notes of the third symposium Logical Formalizations of Commonsense Reasoning, pages 15--24.

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