Invariant-free deduction systems for temporal logic

In this thesis we propose a new approach to deduction methods for temporal logic. Our proposal is based on an inductive definition of eventualities that is different from the usual one. On the basis of this non-customary inductive definition for eventualities, we first provide dual systems of tableaux and sequents for Propositional Linear-time Temporal Logic (PLTL). Then, we adapt the deductive approach introduced by means of these dual tableau and sequent systems to the resolution framework and we present a clausal temporal resolution method for PLTL. Finally, we make use of this new clausal temporal resolution method for establishing logical foundations for declarative temporal logic programming languages. The key element in the deduction systems for temporal logic is to deal with eventualities and hidden invariants that may prevent the fulfillment of eventualities. Different ways of addressing this issue can be found in the works on deduction systems for temporal logic. Traditional tableau systems for temporal logic generate an auxiliary graph in a first pass.Then, in a second pass, unsatisfiable nodes are pruned. In particular, the second pass must check whether the eventualities are fulfilled. The one-pass tableau calculus introduced by S. Schwendimann requires an additional handling of information in order to detect cyclic branches that contain unfulfilled eventualities. Regarding traditional sequent calculi for temporal logic, the issue of eventualities and hidden invariants is tackled by making use of a kind of inference rules (mainly, invariant-based rules or infinitary rules) that complicates their automation. A remarkable consequence of using either a two-pass approach based on auxiliary graphs or aone-pass approach that requires an additional handling of information in the tableau framework, and either invariant-based rules or infinitary rules in the sequent framework, is that temporal logic fails to carry out the classical correspondence between tableaux and sequents. In this thesis, we first provide a one-pass tableau method TTM that instead of a graph obtains a cyclic tree to decide whether a set of PLTL-formulas is satisfiable. In TTM tableaux are classical-like. For unsatisfiable sets of formulas, TTM produces tableaux whose leaves contain a formula and its negation. In the case of satisfiable sets of formulas, TTM builds tableaux where each fully expanded open branch characterizes a collection of models for the set of formulas in the root. The tableau method TTM is complete and yields a decision procedure for PLTL. This tableau method is directly associated to a one-sided sequent calculus called TTC. Since TTM is free from all the structural rules that hinder the mechanization of deduction, e.g. weakening and contraction, then the resulting sequent calculus TTC is also free from this kind of structural rules. In particular, TTC is free of any kind of cut, including invariant-based cut. From the deduction system TTC, we obtain a two-sided sequent calculus GTC that preserves all these good freeness properties and is finitary, sound and complete for PLTL. Therefore, we show that the classical correspondence between tableaux and sequent calculi can be extended to temporal logic. The most fruitful approach in the literature on resolution methods for temporal logic, which was started with the seminal paper of M. Fisher, deals with PLTL and requires to generate invariants for performing resolution on eventualities. In this thesis, we present a new approach to resolution for PLTL. The main novelty of our approach is that we do not generate invariants for performing resolution on eventualities. Our method is based on the dual methods of tableaux and sequents for PLTL mentioned above. Our resolution method involves translation into a clausal normal form that is a direct extension of classical CNF. We first show that any PLTL-formula can be transformed into this clausal normal form. Then, we present our temporal resolution method, called TRS-resolution, that extends classical propositional resolution. Finally, we prove that TRS-resolution is sound and complete. In fact, it finishes for any input formula deciding its satisfiability, hence it gives rise to a new decision procedure for PLTL. In the field of temporal logic programming, the declarative proposals that provide a completeness result do not allow eventualities, whereas the proposals that follow the imperative future approach either restrict the use of eventualities or deal with them by calculating an upper bound based on the small model property for PLTL. In the latter, when the length of a derivation reaches the upper bound, the derivation is given up and backtracking is used to try another possible derivation. In this thesis we present a declarative propositional temporal logic programming language, called TeDiLog, that is a combination of the temporal and disjunctive paradigms in Logic Programming. We establish the logical foundations of our proposal by formally defining operational and logical semantics for TeDiLog and by proving their equivalence. Since TeDiLog is, syntactically, a sublanguage of PLTL, the logical semantics of TeDiLog is supported by PLTL logical consequence. The operational semantics of TeDiLog is based on TRS-resolution. TeDiLog allows both eventualities and always-formulas to occur in clause heads and also in clause bodies. To the best of our knowledge, TeDiLog is the first declarative temporal logic programming language that achieves this high degree of expressiveness. Since the tableau method presented in this thesis is able to detect that the fulfillment of an eventuality is prevented by a hidden invariant without checking for it by means of an extra process, since our finitary sequent calculi do not include invariant-based rules and since our resolution method dispenses with invariant generation, we say that our deduction methods are invariant-free.

Reasoning about Temporal Context using Ontology and Abductive Constraint Logic Programming

The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.

Reasoning about Temporal Context using Ontology and Abductive Constraint Logic Programming

The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.

Reasoning about Temporal Context using Ontology and Abductive Constraint Logic Programming

The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.

Reasoning about Temporal Context using Ontology and Abductive Constraint Logic Programming

The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.

Control of dynamical systems with temporal logic specifications

This thesis is motivated by safety-critical applications involving autonomous air, ground, and space vehicles carrying out complex tasks in uncertain and adversarial environments. We use temporal logic as a language to formally specify complex tasks and system properties. Temporal logic specifications generalize the classical notions of stability and reachability that are studied in the control and hybrid systems communities. Given a system model and a formal task specification, the goal is to automatically synthesize a control policy for the system that ensures that the system satisfies the specification. This thesis presents novel control policy synthesis algorithms for optimal and robust control of dynamical systems with temporal logic specifications. Furthermore, it introduces algorithms that are efficient and extend to high-dimensional dynamical systems.

The first contribution of this thesis is the generalization of a classical linear temporal logic (LTL) control synthesis approach to optimal and robust control. We show how we can extend automata-based synthesis techniques for discrete abstractions of dynamical systems to create optimal and robust controllers that are guaranteed to satisfy an LTL specification. Such optimal and robust controllers can be computed at little extra computational cost compared to computing a feasible controller.

The second contribution of this thesis addresses the scalability of control synthesis with LTL specifications. A major limitation of the standard automaton-based approach for control with LTL specifications is that the automaton might be doubly-exponential in the size of the LTL specification. We introduce a fragment of LTL for which one can compute feasible control policies in time polynomial in the size of the system and specification. Additionally, we show how to compute optimal control policies for a variety of cost functions, and identify interesting cases when this can be done in polynomial time. These techniques are particularly relevant for online control, as one can guarantee that a feasible solution can be found quickly, and then iteratively improve on the quality as time permits.

The final contribution of this thesis is a set of algorithms for computing feasible trajectories for high-dimensional, nonlinear systems with LTL specifications. These algorithms avoid a potentially computationally-expensive process of computing a discrete abstraction, and instead compute directly on the system's continuous state space. The first method uses an automaton representing the specification to directly encode a series of constrained-reachability subproblems, which can be solved in a modular fashion by using standard techniques. The second method encodes an LTL formula as mixed-integer linear programming constraints on the dynamical system. We demonstrate these approaches with numerical experiments on temporal logic motion planning problems with high-dimensional (10+ states) continuous systems.

Conflict-Tolerant Real-Time Specifications in Metric Temporal Logic

A framework based on the notion of "conflict-tolerance" was proposed in as a compositional methodology for developing and reasoning about systems that comprise multiple independent controllers. A central notion in this framework is that of a "conflict-tolerant" specification for a controller. In this work we propose a way of defining conflict-tolerant real-time specifications in Metric Interval Temporal Logic (MITL). We call our logic CT-MITL for Conflict-Tolerant MITL. We then give a clock optimal "delay-then-extend" construction for building a timed transition system for monitoring past-MITL formulas. We show how this monitoring transition system can be used to solve the associated verification and synthesis problems for CT-MITL.

A decidable temporal logic with repeating values

Various logical formalisms with the freeze quantifier have been recently considered to model computer systems even though this is a powerful mechanism that often leads to undecidability. In this paper, we study a linear-time temporal logic with past-time operators such that the freeze operator is only used to express that some value from an infinite set is repeated in the future or in the past. Such a restriction has been inspired by a recent work on spatio-temporal logics. We show decidability of finitary and infinitary satisfiability by reduction into the verification of temporal properties in Petri nets. This is a surprising result since the logic is closed under negation, contains future-time and past-time temporal operators and can express the nonce property and its negation. These ingredients are known to lead to undecidability with a more liberal use of the freeze quantifier.

Incremental Control Synthesis for Robotics in the Presence of Temporal Logic Specifications

This thesis presents methods for incrementally constructing controllers in the presence of uncertainty and nonlinear dynamics. The basic setting is motion planning subject to temporal logic specifications. Broadly, two categories of problems are treated. The first is reactive formal synthesis when so-called discrete abstractions are available. The fragment of linear-time temporal logic (LTL) known as GR(1) is used to express assumptions about an adversarial environment and requirements of the controller. Two problems of changes to a specification are posed that concern the two major aspects of GR(1): safety and liveness. Algorithms providing incremental updates to strategies are presented as solutions. In support of these, an annotation of strategies is developed that facilitates repeated modifications. A variety of properties are proven about it, including necessity of existence and sufficiency for a strategy to be winning. The second category of problems considered is non-reactive (open-loop) synthesis in the absence of a discrete abstraction. Instead, the presented stochastic optimization methods directly construct a control input sequence that achieves low cost and satisfies a LTL formula. Several relaxations are considered as heuristics to address the rarity of sampling trajectories that satisfy an LTL formula and demonstrated to improve convergence rates for Dubins car and single-integrators subject to a recurrence task.

Application of Inductive Logic Programming to Structure-Based Drug Design

Enot, D. and King, R. D. (2003) Application of Inductive Logic Programming to Structure-Based Drug Design. 7th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD '03). Springer LNAI 2838 p156-167

An Empirical Study of the Use of Relevance Information in Inductive Logic Programming

Srinivasan, A., King, R. D. and Bain, M.E. (2003) An Empirical Study of the Use of Relevance Information in Inductive Logic Programming. Journal of Machine Learning Research. 4(Jul):369-383

Structure based drug design with inductive logic programming

David P. Enot and Ross D. King (2003). Structure based drug design with inductive logic programming. The ACS National Meeting Spring 2003, New Orleans

The use of Inductive Logic Programming in drug design

David P. Enot and Ross D. King (2002) The use of Inductive Logic Programming in drug design. Proceedings of the 14th EuroQSAR Symposium (EuroQSAR 2002). Blackwell Publishing, p247-250