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Linear Temporal Logic and Linear Dynamic Logic on Finite Traces
, 2013
"... In this paper we look into the assumption of interpreting LTL over finite traces. In particular we show that LTLf, i.e., LTL under this assumption, is less expressive than what might appear at first sight, and that at essentially no computational cost one can make a significant increase in expressiv ..."
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In this paper we look into the assumption of interpreting LTL over finite traces. In particular we show that LTLf, i.e., LTL under this assumption, is less expressive than what might appear at first sight, and that at essentially no computational cost one can make a significant increase in expressiveness while maintaining the same intuitiveness of LTLf. Indeed, we propose a logic, LDLf for Linear Dynamic Logic over finite traces, which borrows the syntax from Propositional Dynamic Logic (PDL), but is interpreted over finite traces. Satisfiability, validity and logical implication (as well as model checking) for LDLf are PSPACEcomplete as for LTLf (and LTL).
Elaborating Requirements using Model Checking and Inductive Learning
"... Abstract—The process of requirements engineering includes many activities, from goal elicitation to requirements specification. The aim is to develop an operational requirements specification that is guaranteed to satisfy the goals. In this paper, we propose a formal, systematic approach for generat ..."
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Abstract—The process of requirements engineering includes many activities, from goal elicitation to requirements specification. The aim is to develop an operational requirements specification that is guaranteed to satisfy the goals. In this paper, we propose a formal, systematic approach for generating a set of operational requirements that are complete with respect to given goals. We show how the integration of model checking and inductive learning can be effectively used to do this. The model checking formally verifies the satisfaction of the goals and produces counterexamples when incompleteness in the operational requirements is detected. The inductive learning process then computes operational requirements from the counterexamples and userprovided positive examples. These learned operational requirements are guaranteed to eliminate the counterexamples and be consistent with the goals. This process is performed iteratively until no goal violation is detected. The proposed framework is a rigorous, toolsupported requirements elaboration technique which is formally guided by the engineer’s knowledge of the domain and the envisioned system. Index Terms—Requirements elaboration, goal operationalisation, behaviour model refinement, model checking, inductive learning. F
Nonclassical Planning with a Classical Planner: The Power of Transformations
"... Abstract. Planning is the modelbased approach to autonomous behavior where a predictive model of actions and sensors is used to generate the behavior for achieving given goals. The main challenges in planning are computational as all models, whether featuring uncertainty and feedback or not, are ..."
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Abstract. Planning is the modelbased approach to autonomous behavior where a predictive model of actions and sensors is used to generate the behavior for achieving given goals. The main challenges in planning are computational as all models, whether featuring uncertainty and feedback or not, are intractable in the worst case when represented in compact form. Classical planning refers to the simplest form of planning where goals are to be achieved by applying deterministic actions to a fully known initial situation. In this invited paper, I review the inferences performed by classical planners that enable them to deal with large problems, and the transformations that have been developed for using these planners to deal with nonclassical features such as soft goals, hidden goals to be recognized, planning with incomplete information and sensing, and multiagent nested beliefs. 1
In Proceedings IJCAI2013 Fair LTL Synthesis for NonDeterministic Systems using Strong Cyclic Planners
"... We consider the problem of planning in environments where the state is fully observable, actions have nondeterministic effects, and plans must generate infinite state trajectories for achieving a large class of LTL goals. More formally, we focus on the control synthesis problem under the assumption ..."
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We consider the problem of planning in environments where the state is fully observable, actions have nondeterministic effects, and plans must generate infinite state trajectories for achieving a large class of LTL goals. More formally, we focus on the control synthesis problem under the assumption that the LTL formula to be realized can be mapped into a deterministic Büchi automaton. We show that by assuming that action nondeterminism is fair, namely that infinite executions of a nondeterministic action in the same state yield each possible successor state an infinite number of times, the (fair) synthesis problem can be reduced to a standard strong cyclic planning task over reachability goals. Since strong cyclic planners are built on top of efficient classical planners, the transformation reduces the nondeterministic, fully observable, temporally extended planning task into the solution of classical planning problems. A number of experiments are reported showing the potential benefits of this approach to synthesis in comparison with stateoftheart symbolic methods. 1
Proceedings of the TwentyThird International Joint Conference on Artificial Intelligence Bounded Epistemic Situation Calculus Theories
"... We define the class of ebounded theories in the epistemic situation calculus, where the number of fluent atoms that the agent thinks may be true is bounded by a constant. Such theories can still have an infinite domain and an infinite set of states. We show that for them verification of an expressi ..."
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We define the class of ebounded theories in the epistemic situation calculus, where the number of fluent atoms that the agent thinks may be true is bounded by a constant. Such theories can still have an infinite domain and an infinite set of states. We show that for them verification of an expressive class of firstorder µcalculus temporal epistemic properties is decidable. We also show that if the agent’s knowledge in the initial situation is ebounded and the objective part of an action theory maintains boundedness, then the entire epistemic theory is ebounded.
LTLf Satisfiability Checking
"... Abstract. We consider here Linear Temporal Logic (LTL) formulas interpreted over finite traces. We denote this logic by LTLf. The existing approach for LTLf satisfiability checking is based on a reduction to standard LTL satisfiability checking. We describe here a novel direct approach to LTLf sat ..."
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Abstract. We consider here Linear Temporal Logic (LTL) formulas interpreted over finite traces. We denote this logic by LTLf. The existing approach for LTLf satisfiability checking is based on a reduction to standard LTL satisfiability checking. We describe here a novel direct approach to LTLf satisfiability checking, where we take advantage of the difference in the semantics between LTL and LTLf. While LTL satisfiability checking requires finding a fair cycle in an appropriate transition system, here we need to search only for a finite trace. This enables us to introduce specialized heuristics, where we also exploit recent progress in Boolean SAT solving. We have implemented our approach in a prototype tool and experiments show that our approach outperforms existing approaches. 1