The Experts below are selected from a list of 4335 Experts worldwide ranked by ideXlab platform

Murray Shanahan - One of the best experts on this subject based on the ideXlab platform.

Nihan Kesim Cicekli - One of the best experts on this subject based on the ideXlab platform.

  • A monolithic approach to automated composition of semantic web services with the Event Calculus
    Knowledge-Based Systems, 2010
    Co-Authors: Cagla Okutan, Nihan Kesim Cicekli
    Abstract:

    In this paper, a web service composition and execution framework is presented for semantically -annotated web services. A monolithic approach to automated web service composition and execution problem is chosen, which provides some benefits by separating composition and execution phases. An AI planning method using a logical formalism, namely Abductive Event Calculus, is chosen for the composition phase. This formalism allows one to generate a narrative of actions and temporal orderings using abductive planning techniques given a goal. The functional properties of services, namely input/output/precondition/effects (IOPE) are taken into consideration in the composition phase and non-functional properties, namely Quality of Service (QoS) parameters are used in selecting the most appropriate solution to be executed. The repository of OWL-S semantic web services are translated to the Event Calculus axioms and the resulting plans found by the Abductive Event Calculus Planner are converted to graphs. These graphs can be sorted according to a score calculated using the defined quality of service parameters of the atomic services in the composition to determine the optimal solution. The selected graph is converted to an OWL-S file which is executed consequently.

  • Automated composition of web services with the abductive Event Calculus
    Information Sciences, 2010
    Co-Authors: Esra Kirci Ozorhan, Esat Kaan Kuban, Nihan Kesim Cicekli
    Abstract:

    This paper proposes the application of the abductive Event Calculus to the web service composition and execution problem. There are different approaches to web service composition, which are suitable for different application scenarios. In this paper, we are concerned with the formalization of both the interleaved and template-based approaches using the Event Calculus framework. First, in the interleaved approach, it is shown that given a set of OWL-S web service descriptions in a service repository and a set of user specified inputs and outputs from domain ontology, the abductive Event Calculus can be used to generate web service compositions and return values for the outputs by executing the necessary web services. Next, in the template-based approach, it is shown that if generic web service compositions are given as templates using OWL-S, they can be translated into the axioms of the Event Calculus and the abductive theorem prover can be used to generate the actual web service compositions which can be executed afterwards.

  • automated web services composition with the Event Calculus
    Engineering Societies in the Agents World VIII, 2008
    Co-Authors: Onur Aydin, Nihan Kesim Cicekli, Ilyas Cicekli
    Abstract:

    As the web services proliferate and complicate it is becoming an overwhelming job to manually prepare the web service compositions which describe the communication and integration between web services. This paper analyzes the usage of the Event Calculus, which is one of the logical action-effect definition languages, for the automated preparation and execution of web service compositions. In this context, abductive planning capabilities of the Event Calculus are utilized. It is shown that composite process definitions in OWL-S can be translated into Event Calculus axioms so that planning with generic process definitions is possible within this framework.

  • Formalizing the specification and execution of workflows using the Event Calculus
    Information Sciences, 2006
    Co-Authors: Nihan Kesim Cicekli, Ilyas Cicekli
    Abstract:

    The Event Calculus is a logic programming formalism for representing Events and their effects especially in database applications. This paper proposes the Event Calculus as a logic-based methodology for the specification and execution of workflows. It is shown that the control flow graph of a workflow specification can be expressed as a set of logical formulas and the Event Calculus can be used to specify the role of a workflow manager through a set of rules for the execution dependencies of activities. The proposed framework for a workflow manager maintains a history of Events to control the execution of activities. The Events are instructions to the workflow manager to coordinate the execution of activities. Based on the already occurred Events, the workflow manager triggers new Events to schedule new activities in accordance with the control flow graph of the workflow. The net effect is an alternative approach for defining a workflow engine whose operational semantics is naturally integrated with the operational semantics of a deductive database. Within this framework it is possible to model sequential and concurrent activities with or without synchronization. It is also possible to model agent assignment and execution of concurrent workflow instances. The paper, thus, contributes a logical perspective to the task of developing formalization for the workflow management systems.

  • Formalizing workflows using the Event Calculus
    Lecture Notes in Computer Science, 2000
    Co-Authors: Nihan Kesim Cicekli, Yakup Yildirim
    Abstract:

    The Event Calculus is a logic programming formalism for representing Events and their effects especially in database applications. This paper presents the use of the Event Calculus for specifying and simulating workflows. The proposed framework maintains a representation of the dynamic world being modeled on the basis of user supplied axioms about preconditions and effects of Events and the initial state of the world. The net effect is that a workflow specification can be made at a higher level of abstraction. Within this framework it is possible to model sequential and concurrent activities with synchronization when necessary. It is also possible to model agent assignment and concurrent workflow instances.

Georgios Paliouras - One of the best experts on this subject based on the ideXlab platform.

  • Parallel online Event Calculus learning for complex Event recognition
    Future Generation Computer Systems, 2019
    Co-Authors: Nikos Katzouris, Alexander Artikis, Georgios Paliouras
    Abstract:

    Abstract Logic-based Event recognition systems infer occurrences of Events in time using a set of Event definitions in the form of first-order rules. The Event Calculus is a temporal logic that has been used as a basis in Event recognition applications, providing, among others, direct connections to machine learning, via Inductive Logic Programming (ILP). OLED  is a recently proposed ILP system that learns Event definitions in the form of Event Calculus theories, in a single pass over a data stream. We present two strategies for parallel online learning with OLED . We evaluate our proposed approaches on three datasets from the domains of activity recognition and maritime surveillance and show that they can significantly reduce training times, while they are capable of achieving super-linear speed-ups under certain circumstances.

  • Reactive Reasoning with the Event Calculus.
    arXiv: Artificial Intelligence, 2015
    Co-Authors: Alexander Artikis, Marek Sergot, Georgios Paliouras
    Abstract:

    Systems for symbolic Event recognition accept as input a stream of time-stamped Events from sensors and other computational devices, and seek to identify high-level composite Events, collections of Events that satisfy some pattern. RTEC is an Event Calculus dialect with novel implementation and 'windowing' techniques that allow for efficient Event recognition, scalable to large data streams. RTEC can deal with applications where Event data arrive with a (variable) delay from, and are revised by, the underlying sources. RTEC can update already recognised Events and recognise new Events when data arrive with a delay or following data revision. Our evaluation shows that RTEC can support real-time Event recognition and is capable of meeting the performance requirements identified in a recent survey of Event processing use cases.

  • Probabilistic Event Calculus for Event recognition
    ACM Transactions on Computational Logic, 2015
    Co-Authors: Anastasios Skarlatidis, Georgios Paliouras, Alexander Artikis, George A. Vouros
    Abstract:

    Symbolic Event recognition systems have been successfully applied to a variety of application domains, extracting useful information in the form of Events, allowing experts or other systems to monitor and respond when significant Events are recognised. In a typical Event recognition application, however, these systems often have to deal with a significant amount of uncertainty. In this paper, we address the issue of uncertainty in logic-based Event recognition by extending the Event Calculus with probabilistic reasoning. Markov Logic Networks are a natural candidate for our logic-based formalism. However, the temporal semantics of the Event Calculus introduce a number of challenges for the proposed model. We show how and under what assumptions we can overcome these problems. Additionally, we study how probabilistic modelling changes the behaviour of the formalism, affecting its key property, the inertia of fluents. Furthermore, we demonstrate the advantages of the probabilistic Event Calculus through examples and experiments in the domain of activity recognition, using a publicly available dataset for video surveillance.

  • A probabilistic logic programming Event Calculus
    Theory and Practice of Logic Programming, 2015
    Co-Authors: Anastasios Skarlatidis, Jason Filippou, Alexander Artikis, Georgios Paliouras
    Abstract:

    We present a system for recognising human activity given a symbolic representation of video content. The input of our system is a set of time-stamped short-term activities (STA) detected on video frames. The output is a set of recognised long-term activities (LTA), which are pre-defined temporal combinations of STA. The constraints on the STA that, if satisfied, lead to the recognition of an LTA, have been expressed using a dialect of the Event Calculus. In order to handle the uncertainty that naturally occurs in human activity recognition, we adapted this dialect to a state-of-the-art probabilistic logic programming framework. We present a detailed evaluation and comparison of the crisp and probabilistic approaches through experimentation on a benchmark dataset of human surveillance videos.

  • probabilistic Event Calculus based on markov logic networks
    Rules and Rule Markup Languages for the Semantic Web, 2011
    Co-Authors: Anastasios Skarlatidis, Georgios Paliouras, George A. Vouros, Alexander Artikis
    Abstract:

    In this paper, we address the issue of uncertainty in Event recognition by extending the Event Calculus with probabilistic reasoning. Markov Logic Networks are a natural candidate for our logic-based formalism. However, the temporal semantics of Event Calculus introduce a number of challenges for the proposed model. We show how and under what assumptions we can overcome these problems. Additionally, we demonstrate the advantages of the probabilistic Event Calculus through examples and experiments in the domain of activity recognition, using a publicly available dataset of video surveillance.

Luca Chittaro - One of the best experts on this subject based on the ideXlab platform.

  • A General Modal Framework for the Event Calculus and its Skeptical and Credulous Variants
    2018
    Co-Authors: Iliano Cervesato, Luca Chittaro, Angelo Montanari
    Abstract:

    We propose a general and uniform modal framework for the Event Calculus (EC) and its skeptical and credulous variants. The resulting temporal formalism, called the Generalized Modal Event Calculus (GMEC), extends considerably the expressive power of EC when information about the ordering of Events is incomplete. It provides means of inquiring about the evolution of the maximal validity intervals of properties relatively to all possible refinements of the ordering data by allowing free mixing of propositional connectives and modal operators. We first give a semantic definition of GMEC; then, we propose a declarative encoding of GMEC in the language of hereditary Harrop formulas and prove the soundness and completeness of the resulting logic programs

  • Temporal Granularity and Indeterminacy in Reasoning About Actions and Change: An Approach Based on the Event Calculus
    Annals of Mathematics and Artificial Intelligence, 2002
    Co-Authors: Luca Chittaro, C. Combi
    Abstract:

    In many real-world applications, temporal information is often imprecise about the temporal location of Events ( indeterminacy ) and comes at different granularities. Formalisms for reasoning about Events and change, such as the Event Calculus (EC) and the Situation Calculus, do not usually provide mechanisms for handling such information, and very little research has been devoted to the goal of extending them with these capabilities. In this paper, we propose TGIC (Temporal Granularity and Indeterminacy Event Calculus), an approach based on the EC ontology to represent Events with imprecise location and to deal with them on different timelines.

  • The Language of Time - A Reader - Extending the Event Calculus with Temporal Granularity and Indeterminacy
    2000
    Co-Authors: Luca Chittaro, C. Combi
    Abstract:

    In many real-world applications, temporal information is often imprecise about the temporal location of Events (indeterminacy) and comes at different granularities. Formalisms for reasoning about Events and change, such as the Event Calculus (EC) and the Situation Calculus, do not usually provide mechanisms for handling such data, and very little research has been devoted to the goal of extending them with these capabilities. In this paper, we propose TGIC (Temporal Granularity and Indeterminacy Event Calculus), an approach to represent Events with imprecise location and to deal with them on different timelines, based on the EC ontology.

  • ARTDB - Temporal Indeterminancy in Deductive Databases: An Approach Based on Event Calculus
    Active Real-Time and Temporal Database Systems, 1998
    Co-Authors: Luca Chittaro, C. Combi
    Abstract:

    In this paper, we deal with the notion of temporal indeterminacy in temporal deductive databases. We adopt Kowalski and Sergot's Event Calculus (1986, 1992) as our data model. To the best of our knowledge, no previous research efforts have been devoted to introduce indeterminacy in the Event Calculus (EC). We first motivate the need for indeterminacy in real world applications. Then, after briefly presenting EC, we illustrate in detail our proposal (TIC, Temporal Indeterminacy Event Calculus). From a description of Events whose precise temporal occurrence is unknown, and a description of the properties initiated or terminated by those Events, TIC derives intervals over which properties are necessarily valid, and intervals of indeterminacy for the initiating and terminating instants of the properties. Although we adopt EC as our ontology, the proposed ideas can be reformulated for adoption in other approaches. TIC is presented both informally and formally, and illustrated with several examples. Finally, we discuss completeness and complexity issues of TIC.

  • EFFICIENT TEMPORAL REASONING IN THE CACHED Event Calculus
    Computational Intelligence, 1996
    Co-Authors: Luca Chittaro, Angelo Montanari
    Abstract:

    This article deals with the problem of providing Kowaiski and Sergot's Event Calculus, extended with context dependency, with an efficient implementation in a logic programming framework. Despite a widespread recognition that a positive solution to efficiency issues is necessary to guarantee the computational feasibility of existing approaches to temporal reasoning, the problem of analyzing the complexity of temporal reasoning programs has been largely overlooked. This article provides a mathematical analysis of the efficiency of query and update processing in the Event Calculus and defines a cached version of the Calculus that (i) moves computational complexity from query to update processing and (ii) features an absolute improvement of performance, because query processing in the Event Calculus costs much more than update processing in the proposed cached version.

Erik T. Mueller - One of the best experts on this subject based on the ideXlab platform.

  • The Event Calculus
    Commonsense Reasoning, 2015
    Co-Authors: Erik T. Mueller
    Abstract:

    We present the foundations of the Event Calculus, a formalism for commonsense reasoning. We review first-order logic and describe some notational conventions. We discuss the basics of the Event Calculus, and we present two axiomatizations of the Event Calculus: EC and DEC. We discuss how to choose which axiomatization to use. We present reification, which is needed to represent statements about Events and fluents in first-order logic. We discuss unique names axioms, conditions, circumscription, and domain descriptions, and we describe the types of reasoning that can be performed using the Event Calculus.

  • The Discrete Event Calculus Reasoner
    Commonsense Reasoning, 2015
    Co-Authors: Erik T. Mueller
    Abstract:

    We describe the Discrete Event Calculus Reasoner, which uses satisfiability (SAT) to solve Event Calculus problems. The program can be used to perform automated deduction, abduction, postdiction, and model finding. We discuss the architecture of the program and the encoding of SAT problems. We present some simple examples of how the program is used and then present a more complicated example. We discuss the language used to describe commonsense reasoning problems to the program.

  • Discrete Event Calculus Deduction using First-Order Automated Theorem Proving
    2008
    Co-Authors: Erik T. Mueller, Geoff Sutcliffe
    Abstract:

    Abstract. The Event Calculus is a powerful and highly usable formalism for reasoning about action and change. The discrete Event Calculus limits time to integers. This paper shows how discrete Event Calculus problems can be encoded in first-order logic, and solved using a first-order logic automated theorem proving system. The following techniques are discussed: reification is used to convert Event and fluent atoms into first-order terms, uniqueness-of-names axioms are generated to ensure uniqueness of Event and fluent terms, predicate completion is used to convert second-order circumscriptions into first-order formulae, and a limited first-order axiomatization of integer arithmetic is developed. The performance of first-order automated theorem proving is compared to that of satisfiability solving.

  • Chapter 17 Event Calculus
    Handbook of Knowledge Representation, 2008
    Co-Authors: Erik T. Mueller
    Abstract:

    Publisher Summary The Event Calculus is a formalism for reasoning about action and change. Like the situation Calculus, the Event Calculus has actions, which are called “Events,” and time-varying properties or fluents. In the situation Calculus, performing an action in a situation gives rise to a successor situation. Situation Calculus actions are hypothetical, and time is tree like. In the Event Calculus, there is a single time line on which actual Events occur. A narrative is a possibly incomplete specification of a set of actual Event occurrences. The Event Calculus is narrative based unlike the standard situation Calculus in which an exact sequence of hypothetical actions is represented. This chapter discusses several versions of the Event Calculus, the use of circumscription in the Event Calculus, methods of knowledge representation using the Event Calculus, automated Event Calculus reasoning, and applications of the Event Calculus. The predicates and functions of the original Event Calculus are described in the chapter.

  • AAAI Spring Symposium: Logical Formalizations of Commonsense Reasoning - Discrete Event Calculus with Branching Time.
    2007
    Co-Authors: Erik T. Mueller
    Abstract:

    We add branching time to the linear discrete Event Calculus, which yields a formalism for commonsense reasoning that combines the benefits of the situation Calculus and the Event Calculus. We characterize the precise relationship between the linear and branching versions of the discrete Event Calculus, and prove that a restricted version of the branching discrete Event Calculus is equivalent to the situation Calculus. We show how the branching discrete Event Calculus can be used to solve commonsense reasoning problems involving hypothetical Events, concurrent Events with cumulative and canceling effects, and triggered Events.