Much previous work in artificial intelligence has neglected representing time in all its complexity. In particular, it has neglected continuous change and the indeterminacy of the future. To rectify this, I have developed a first-order temporal logic, in which it is possible to name and prove things about facts, events, plans, and world histories. In particular, the logic provides analyses of causality, continuous change in quantities, the persistence of facts (the frame problem), and the relationship between tasks and actions. It may be possible to implement a temporal-inference machine based on this logic, which keeps track of several “maps” of a time line, one per possible history.

A Temporal Logic for Reasoning about Processes and Plans.

BPMN: An introduction to the standard

This collection represents the primary reference work for researchers and students in the area of Temporal Reasoning in Artificial Intelligence Temporal reasoning has a vital role to play in many areas, particularly Artificial Intelligence Yet, until now, there has been no single volume collecting together the breadth of work in this area This collection brings together the leading researchers in a range of relevant areas and provides an coherent description of the breadth of activity concerning temporal reasoning in the filed of Artificial Intelligence

Key Features:

- Broad range: foundations; techniques and applications
- Leading researchers around the world have written the chapters
- Covers many vital applications
- Source book for Artificial Intelligence, temporal reasoning
- Approaches provide foundation for many future software systems

·Broad range: foundations; techniques and applications
·Leading researchers around the world have written the chapters
·Covers many vital applications
·Source book for Artificial Intelligence, temporal reasoning
·Approaches provide foundation for many future software systems

Table of Contents

"Formal Theories of Time and Temproal Incidence", Lluis Vila 

"Eventualities", Antony Galton 

"Time Granularity", Jerome Euzenat and Angelo Montanari 

"Modal Varieties of Temporal Logic", Howard Barringer and Dov Gabbay 

"Temporal Qualification in Artificial Intelligence", Han Reichgelt and Lluis Vila 

"Computational Complexity of Temporal Constraint Problems", Thomas Drakengren and Peter Jonsson 

"Indefinite Constraint Databases with Temporal Information: Representational Power and Computational Complexity", Manolis Koubarakis 

"Processing Qualitative Temporal Constraints", Alfonso Gerevini 

"Theorem-Proving for Discrete Temporal Logic", Mark Reynolds/Clare Dixon 

"Probabilistic Temporal Reasoning", Steve Hanks/David Madigan 

"Temporal Reasoning with iff-Abduction", Marc Denecker/Kristof Van Belleghem 

"Temporal Description Logics", Alessandro Artale/Enrico Franconi 

"Logic Programming and Reasoning about Actions", Chitta Baral/Michael Gelfond 

"Temporal Databases" Jan Chomicki/David Toman 

"Temporal Reasoning in Agent-Based Systems" Michael Fisher/Michael Wooldridge 

"Time in Planning" Maris Fox/Derek Long 

"Time in Automated Legal Reasoning" Lluis Vila/Hajime Yoshino 

"Temporal Reasoning in Natural Language" Alice ter Meulen 

"Temporal Reasoning in Medicine" Elpida Keravnou/Yuval Shahar 

"Time in Qualitative Simulation" Dan Clancy/Benjamin Kuipers

Handbook of Temporal Reasoning in Artificial Intelligence

We propose a method for using the World Wide Web to acquire trigram estimates for statistical language modeling. We submit an N-gram as a phrase query to Web search engines. The search engines return the number of Web pages containing the phrase, from which the N-gram count is estimated. The N-gram counts are then used to form Web-based trigram probability estimates. We discuss the properties of such estimates, and methods to interpolate them with traditional corpus based trigram estimates. We show that the interpolated models improve speech recognition word error rate significantly over a small test set.

/pdf/improving-trigram-language-modeling-with-the-world-wide-web-4r1z50wcyq.pdf

Improving trigram language modeling with the World Wide Web

Although the security of Cyber-Physical Systems (CPS) has been recently receiving significant attention from the research community, undoubtedly, there still exists a substantial lack of a comprehensive and a holistic understanding of attackers’ malicious strategies, aims and intentions. To this end, this paper uniquely exploits passive monitoring and analysis of a newly deployed network telescope IP address space in a first attempt ever to build broad notions of real CPS maliciousness. Specifically, we approach this problem by inferring, investigating, characterizing and reporting large-scale probing activities that specifically target more than 20 diverse, heavily employed CPS protocols. To permit such analysis, we initially devise and evaluate a novel probabilistic model that aims at filtering noise that is embedded in network telescope traffic. Subsequently, we generate amalgamated statistics, inferences and insights characterizing such inferred scanning activities in terms of their probe types, the distribution of their sources and their packets’ headers, among numerous others, in addition to examining and visualizing the co-occurrence patterns of such events. Further, we propose and empirically evaluate an innovative hybrid approach rooted in time-series analysis and context triggered piecewise hashing to infer, characterize and cluster orchestrated and well-coordinated probing activities targeting CPS protocols, which are generated from Internet-scale unsolicited sources. Our analysis and evaluations, which draw upon extensive network telescope data observed over a recent one month period, demonstrate a staggering 33 thousand probes towards ample of CPS protocols, the lack of interest in UDP-based CPS services, and the prevalence of probes towards the ICCP and Modbus protocols. Additionally, we infer a considerable 74% of CPS probes that were persistent throughout the entire analyzed period targeting prominent protocols such as DNP3 and BACnet. Further, we uncover close to 9 thousand large-scale, stealthy, previously undocumented orchestrated probing events targeting a number of such CPS protocols. We validate the various outcomes through cross-validations against publicly available threat repositories. We concur that the devised approaches, techniques, and methods provide a solid first step towards better comprehending real CPS unsolicited objectives and intents.

Internet-scale Probing of CPS: Inference, Characterization and Orchestration Analysis.

A probabilistic temporal interval network is a constraint satisfaction problem where the nodes are temporal intervals and the edges are uncertain interval relations. We attach a probability to each of Allen's basic interval relations. An uncertain relation between two temporal intervals is represented as a disjunction of Allen's probabilistic basic relations. Using the operations of inversion, composition, and addition, defined for this probabilistic representation, we present a path consistency algorithm.

Probabilistic temporal interval networks

Purpose – To measure the exact size of the world wide web (i.e. a census). The measure used is the number of publicly accessible web servers on port 80.Design/methodology/approach – Every IP address on the internet is queried for the presence of a web server.Findings – The census found 18,560,257 web servers.Research limitations/implications – Any web servers hidden behind a firewall, or that did not respond within a reasonable amount of time (20 seconds) were not counted by the census.Practical implications – Whenever a server is found, we download and store a copy of its homepage. The resulting database of homepages is a historical snapshot of the web which will be mined for information in the future.Originality/value – Past web surveys performed by various research groups were only estimates of the size of the web. This is the first time its size has been exactly measured.

World's first web census

We present a multi-agent distributed temporal scheduling system based on probabilistic Interval Algebra networks (i.e., PIA networks). The overall goal is to make each agentâ€™s network consistent and optimal. Each agent is independent and has sole control over its network. But, it must communicate and coordinate with other agents when modifying or updating shared edges. We present an algorithm which allows the agents to collaboratively solve and recommend a temporal schedule. At the agent level, this schedule is optimal under the given local constraints. Although the global solution may not be optimal, we try to generate near optimal ones. Note that our distributed system is not centrally controlled. We use our system to solve scheduling problems from a university problem domain. We also describe the implementation of our proposed system which uses Java, JXTA, and JGraph.

A Multi-Agent Temporal Constraint Satisfaction System Based on Allen's Interval Algebra and Probabilities

We propose a domain independent framework for computer based instruction systems capable of generating custom courses. A salient property of our framework is that the corpus content, pedagogical course structure, and course delivery are independent. The system does not use a student model. We believe that the student is the best model of himself and provide him with the power to dynamically change the course's delivery.

A Highly Flexible Student Driven Architecture for Computer Based Instruction

We define the interval representation problem as the problem of representing the relationships which exist between the truth of an assertion over an interval and the truth of an assertion (either the same or a different one) over its internal points and/or subintervals. For example, “ran a mile without stopping” is true over an interval if and only if “running” is true at each point in the interval and the distance travelled due to “running” equals a mile. There is a relationship between “ran a mile without stopping” over an interval and “running” at the interval's interior points. the interval representation problem is a fundamental problem that must be addressed by first-order temporal logics. In this article, we look at previous attempts to solve the problem and conclude that it remains an open problem. We present a first-order temporal logic called GCH and discuss its approach to the interval representation problem. GCH uses a different approach for representing information associated with an interval. We do not directly associate these assertions with intervals. the representation of these assertions is based on the assumption that what is true at every point in an interval completely determines what is true over the interval. We use the Riemann integral to represent interval-based information.

The interval representation problem

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