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A Planner Fully Based on Linear Time Logic
 In Proc. of AIPS2000
, 2000
"... This work aims at verifying the effective possibility of using Linear Time Logic (LTL) as a planning language. The main advantage of such a rich and expressive language is the possibility of encoding problem specific information, that can be of help both in reducing the search space and finding a be ..."
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Cited by 8 (4 self)
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This work aims at verifying the effective possibility of using Linear Time Logic (LTL) as a planning language. The main advantage of such a rich and expressive language is the possibility of encoding problem specific information, that can be of help both in reducing the search space and finding a better plan. To this purpose, we have implemented a planning system, Padok (Planning with Domain Knowledge), where the whole planning domain is modelled in LTL and planning is reduced to model search. We briefly describe the components of problem specifications accepted by Padok, that may include knowledge about the domain and control knowledge, in a declarative format. Some experiments are then reported, comparing the performances of Padok with some well established existing planners (IPP, BLACKBOX and STAN) on some sample problems. In most cases, our system is guided by additional knowledge that cannot be stated in the languages accepted by the other planners. In general, whe...
First Order Linear Temporal Logic over finite temporal structures is not semidecidable
"... Introduction The model of time underlying Linear Temporal Logic (LTL) is a discrete, linear sequence of states, usually taken to be bounded in the past and innite in the future. In other words, the set of time points is isomorphic to IN. In the propositional case, several sound, complete and termin ..."
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Cited by 7 (2 self)
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Introduction The model of time underlying Linear Temporal Logic (LTL) is a discrete, linear sequence of states, usually taken to be bounded in the past and innite in the future. In other words, the set of time points is isomorphic to IN. In the propositional case, several sound, complete and terminating proofsystems for LTL have been provided; see for instance [6, 5, 3, 2]. In [1] the problem of the existence of a complete recursive axiomatization for the rstorder version of LTL containg the following temporal operators: 2 (\always in the future"), 3 (\eventually"), (\next"), U (\until") and P (\precedes"), equipped with the innite semantics, is studied. It is proved that such an axiomatization cannot exists. The proof makes use of the notion of 1 1 formulae, that is formulae having the form: 8R 1 : : :
Linear temporal logic as an executable semantics for planning languages
 Journal of Logic, Lang and Information
"... This is a draft version of a paper appeared on the Journal of Logic, Language and Information. It should not be cited, quoted or reproduced. This paper presents an approach to artificial intelligence planning based on linear temporal logic (LTL). A simple and easytouse planning language is describ ..."
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Cited by 4 (0 self)
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This is a draft version of a paper appeared on the Journal of Logic, Language and Information. It should not be cited, quoted or reproduced. This paper presents an approach to artificial intelligence planning based on linear temporal logic (LTL). A simple and easytouse planning language is described, PDDLK (Planning Domain Description Language with control Knowledge), which allows one to specify a planning problem together with heuristic information that can be of help for both pruning the search space and finding better quality plans. The semantics of the language is given in terms of a translation into a set of LTL formulae. Planning is then reduced to “executing ” the LTL encoding, i.e. to model search in LTL. The feasibility of the approach has been successfully tested by means of the system Pdk, an implementation of the proposed method. 1
GOAL as a planning formalism
 In Proc. of MATES, volume 5774 of LNCS
, 2009
"... Abstract. It has been observed that there are interesting relations between planning and agent programming. This is not surprising as agent programming was partially motivated by the lack of planners that are able to operate in dynamic, complex environments. Vice versa it has also been observed, how ..."
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Cited by 4 (1 self)
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Abstract. It has been observed that there are interesting relations between planning and agent programming. This is not surprising as agent programming was partially motivated by the lack of planners that are able to operate in dynamic, complex environments. Vice versa it has also been observed, however, that agent programming languages typically lack planning capabilities. We show in this paper that the agent programming language Goal is not only a programming language but can actually be used as a planning formalism as well. This opens up many possibilities for various approaches to mix execution and planning in agentoriented programming. Moreover, by using the recently introduced temporal Goal we are able to include not only the stratified axioms and ADL that are part of PDDL but also plan constraints. 1
Formal Synthesis of Embedded Control Software: Application to Vehicle Management Systems
"... Motivated by the transition from federated to integrated architectures in aerial vehicles, we propose an automated methodology for the synthesis of correctbyconstruction control protocols for vehicle management systems. We use linear temporal logic as the specification language for precisely descr ..."
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Cited by 3 (3 self)
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Motivated by the transition from federated to integrated architectures in aerial vehicles, we propose an automated methodology for the synthesis of correctbyconstruction control protocols for vehicle management systems. We use linear temporal logic as the specification language for precisely describing correct behaviors of the system as well as the admissible dynamic behavior of the environment due to, for example, wind gusts and changes in the flight conditions. We apply the method in the context of dynamic power allocation between a number of subsystems of varying flightcriticality. The resulting power management protocol is guaranteed to be correct, with respect to the overall system specification, for all admissible environment profiles. This approach also enables reasoning about design tradeoffs such as between efficiency (imposed through formal specifications) and system weight (characterized by the amount of required power generation and energy storage). We present our preliminary results in a simple setting and discuss extensions of the methodology to capture more realistic system and environment models and specifications. I.
Propagating Temporal Relations of Intervals by Matrix
 Applied Artificial Intelligence
, 2002
"... Traditional temporal relations propagating is based on Allen ’ s Interval Algebra. This paper proposes an alternative method to propagate temporal relations among intervals, in which 5 £ 5 matrices are used to represent temporal relations of intervals. Hence, the propagation of temporal relations is ..."
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Cited by 2 (2 self)
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Traditional temporal relations propagating is based on Allen ’ s Interval Algebra. This paper proposes an alternative method to propagate temporal relations among intervals, in which 5 £ 5 matrices are used to represent temporal relations of intervals. Hence, the propagation of temporal relations is transformed into a numerical computation. For ef ® ciency, we use the special values of the thirteen matrices to determine the possible temporal relations between two given intervals by using only the ® nal resultant matrix so as to optimize the propagation. To evaluate the utility of the proposed technique, we have implemented the matrix representation in Java. The experimental results demonstrate that the approach is ef ® cient and promising. In the real world, changes cannot be avoided. To conquer and exploit the real world for our life, we must catch the properties of time. So, Allen proposed a time world model of time interval (simply called interval) calculusÐ Interval Algebra (IA) (Allen 1983). The model divides the relationships among intervals into 13 kinds of temporal forms, laying a foundation for dealing with temporal relationships in applications. The major challenge in IA is the propagation of temporal relations. To confront this problem, traditional models are designed to improve IA. For example, a number of researches have been focused on constraint satisfactory
The Main Features of a Planner Fully Based on LTL
 Workshop on ModelTheoretic Approaches to Planning (AIPS2000
, 2000
"... In this work we describe a prototype system, Padok (Planning with Domain Knowledge), where the whole planning domain is modelled in Linear Time Logic (LTL) and planning is reduced to model search. The problem specification accepted by the system can include problem specific information, in a declara ..."
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Cited by 1 (0 self)
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In this work we describe a prototype system, Padok (Planning with Domain Knowledge), where the whole planning domain is modelled in Linear Time Logic (LTL) and planning is reduced to model search. The problem specification accepted by the system can include problem specific information, in a declarative format. The work briey resumes and extends (Cialdea Mayer et al. 2000), showing, through a complete example, how LTL is effectively used as a planning language.
Taming the Complexity of Temporal Epistemic Reasoning
"... Abstract. Temporal logic of knowledge is a combination of temporal and epistemic logic that has been shown to be very useful in areas such as distributed systems, security, and multiagent systems. However, the complexity of the logic can be prohibitive. We here develop a refined version of such a l ..."
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Cited by 1 (0 self)
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Abstract. Temporal logic of knowledge is a combination of temporal and epistemic logic that has been shown to be very useful in areas such as distributed systems, security, and multiagent systems. However, the complexity of the logic can be prohibitive. We here develop a refined version of such a logic and associated tableau procedure with improved complexity but where important classes of specification can still be described. This new logic represents a combination of an “exactly one ” temporal logic with an S5 multimodal logic again restricted to the “exactly one ” form. 1
A Tableau Calculus for First Order Linear Temporal Logic over Bounded Time Structures
"... Introduction The model of time underlying Linear Temporal Logic (LTL) is a discrete, linear sequence of states, usually taken to be bounded in the past and innite in the future. In other words, the set of time points is isomorphic to IN. Dierent sets of temporal operators may be considered: mainly, ..."
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Introduction The model of time underlying Linear Temporal Logic (LTL) is a discrete, linear sequence of states, usually taken to be bounded in the past and innite in the future. In other words, the set of time points is isomorphic to IN. Dierent sets of temporal operators may be considered: mainly, future time operators (2: always, 3: eventually, : next, U : until), possibly restricting to the fragment with 2 and 3 only, or both past and future time ones (\full" LTL). In the propositional case, several sound, complete and terminating proofsystems for LTL have been provided; see for instance [12, 11, 3, 2]. Not much work has been done on the rstorder case. In [9] a normal form theorem for rstorder LTL formulae is proved, but no proofsystem is provided. As far as rst order LTL, equipped with the i
Contingency Planning in Linear Time Logic
"... establishes a correspondence between planning problems and logical theories, and, consequently, between plans and models. This work proposes a similar framework for contingency planning: considering contingent planning problems where the sources of indeterminism are incomplete knowledge about t ..."
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establishes a correspondence between planning problems and logical theories, and, consequently, between plans and models. This work proposes a similar framework for contingency planning: considering contingent planning problems where the sources of indeterminism are incomplete knowledge about the initial state, noninertial fluents and nondeterministic actions, it shows how to encode such problems into Linear Time Logic. Exploiting the semantics of the logic, and the notion of conditioned model introduced in this work, formal characterizations are given of the notions of contingent plan (a plan together with the set of conditions that ensure its executability).