Alexander Artikis

KR Conference 2025 System Paper

A Tensor-Based Probabilistic Event Calculus

• Efthimis Tsilionis
• Alexander Artikis
• Georgios Paliouras

Complex Event Recognition (CER) systems receive as input a stream of time-stamped events and identify situations of interest that satisfy a given pattern. Streaming environments are characterized by the high rate and volume of input data, and thus, scalability is of crucial importance. At the same time, noise and uncertainty are ubiquitous in temporal data, and not considering them, leads to erroneous detections. To confront these challenges, we present a tensor-based formalization of the Event Calculus (EC) for probabilistic inference, and demonstrate the scalability of our approach with the use of CER datasets from two real-world application domains. Moreover, we demonstrate the benefits of our approach, in terms of processing time, by comparing it against a probabilistic logic programming implementation of EC.

I&C Journal 2025 Journal Article

Composite event recognition with arbitrary specifications

• Periklis Mantenoglou
• Alexander Artikis

Composite event recognition (CER) frameworks reason over streams of low-level, symbolic events in order to detect instances of spatio-temporal patterns defining high-level, composite activities. The Event Calculus is a temporal, logical formalism that has been used to define composite activities in CER, while RTEC∘ is a formal CER framework that detects composite activities based on their Event Calculus definitions. RTEC∘, however, cannot handle arbitrary Event Calculus definitions for composite activities, limiting the range of CER applications supported by RTEC∘. We propose RTEC f l, an extension of RTEC∘ that supports arbitrary composite activity specifications in the Event Calculus. We present the syntax, semantics, reasoning algorithms and time complexity of RTEC f l. Moreover, we propose a compiler for RTEC f l, generating the optimal representation of an input set of Event Calculus definitions. We demonstrate the correctness of our compiler and outline its time complexity. We conducted an empirical evaluation of RTEC f l on synthetic and real data streams from human activity recognition and maritime situational awareness, including a comparison with two state-of-the-art Event Calculus-based systems, which demonstrates the benefits of RTEC f l.

TIME Conference 2025 Conference Paper

Prompting LLMs for the Run-Time Event Calculus (Short Paper)

• Andreas Kouvaras
• Periklis Mantenoglou
• Alexander Artikis

Composite activity recognition systems analyse streams of low-level, symbolic events to identify instances of complex activities based on their formal definitions. Crafting these definitions is a challenging task, as it often requires specifying intricate spatio-temporal constraints, and acquiring labeled data for automated learning is difficult. To address this challenge, we introduce a method that leverages pre-trained Large Language Models (LLMs) to generate composite activity definitions, in the language of the Run-Time Event Calculus, from natural language descriptions.

JAIR Journal 2025 Journal Article

Reasoning over Streams of Events with Delayed Effects

• Periklis Mantenoglou
• Manolis Pitsikalis
• Alexander Artikis

In streaming applications, it is often required to detect situations of interest, by means of temporal pattern matching, with minimal latency. In the maritime domain, e.g., where it is crucial to prevent activities that are harmful to the environment, we need to report illegal fishing activities, based on streams of low-level vessel actions, as soon as possible. Streams often include events with delayed effects. In multi-agent voting protocols, e.g., a proposed motion may be seconded at the latest by some time in the future. In simulations of biological systems, a signal may lead to the deactivation of the functions of a gene after a time delay. We propose a formal computational framework that handles streams including events with delayed effects. We present the syntax, semantics and reasoning algorithms of our proposed framework, and demonstrate its correctness and complexity. Furthermore, we present a reproducible analysis on large synthetic and real data streams, from the fields of composite event recognition, multi-agent systems and biological feedback processes, and compare the efficiency of our approach with state-of-the-art systems that can perform stream reasoning in these domains. Our results demonstrate that our framework is capable of reasoning over very large streams, including events with delayed effects, while outperforming the state-of-the-art, often by orders of magnitude.

ECAI Conference 2025 Conference Paper

Sequencing in the Run-Time Event Calculus

• Periklis Mantenoglou
• Alexander Artikis

Composite event recognition (CER) systems detect instances of composite activities over streams of timestamped events. A fundamental operator for CER is ‘sequencing’, expressing that two activities take place one after the other. There is no consensus on a universal definition for sequencing. We provide a set of required properties for a sequencing operator for CER, i. e. , an interval-based semantics, required for durative activities, and associativity, required to express activity hierarchies. We propose a sequencing operator that satisfies all requirements, as opposed to the ones in the literature, and we implement our operator in the CER engine RTEC. We compare our operator both theoretically and empirically with state-of-the-art approaches, demonstrating its benefits and limitations.

AAAI Conference 2025 Conference Paper

Temporal Specification Optimisation for the Event Calculus

• Periklis Mantenoglou
• Alexander Artikis

Temporal pattern matching tasks require the detection of situations of interest based on streams of symbolic events. The Run-Time Event Calculus (RTEC) is a formal framework that represents situations of interest as time-varying properties called 'fluents'. Temporal patterns often express 'Boolean combinations' of situations; RTEC features two types of fluents that may model such patterns: 'simple' and 'statically determined'. A simple fluent representation, however, is exponentially larger and more expensive to reason with than the corresponding statically determined fluent one. We formally identify the class of simple fluent definitions that can be translated into statically determined fluent definitions. Moreover, we present a compiler for the translation, and a reproducible empirical evaluation on real applications.

IJCAI Conference 2024 Conference Paper

A Tensor-Based Formalization of the Event Calculus

• Efthimis Tsilionis
• Alexander Artikis
• Georgios Paliouras

We present a formalization of the Event Calculus (EC) in tensor spaces. The motivation for a tensor-based predicate calculus comes from the area of composite event recognition (CER). As a CER engine, we adopt a logic programming implementation of EC with optimizations for continuous narrative assimilation on data streams. We show how to evaluate EC rules algebraically and solve a linear equation to compute the corresponding models. We demonstrate the scalability of our approach with the use of large datasets from a real-world application domain, and show it outperforms significantly symbolic EC, in terms of processing time.

TIME Conference 2024 Conference Paper

Extending the Range of Temporal Specifications of the Run-Time Event Calculus

• Periklis Mantenoglou
• Alexander Artikis

Composite event recognition (CER) frameworks reason over streams of low-level, symbolic events in order to detect instances of spatio-temporal patterns defining high-level, composite activities. The Event Calculus is a temporal, logical formalism that has been used to define composite activities in CER, while RTEC_{∘} is a formal CER framework that detects composite activities based on their Event Calculus definitions. RTEC_{∘}, however, cannot handle every possible set of Event Calculus definitions for composite activities, limiting the range of CER applications supported by RTEC_{∘}. We propose RTEC_{fl}, an extension of RTEC_{∘} that supports arbitrary composite activity specifications in the Event Calculus. We present the syntax, semantics, reasoning algorithms and time complexity of RTEC_{fl}. Our analysis demonstrates that RTEC_{fl} extends the scope of RTEC_{∘}, supporting every possible set of Event Calculus definitions for composite activities, while maintaining the high reasoning efficiency of RTEC_{∘}.

KR Conference 2023 Conference Paper

Complex Event Recognition with Allen Relations

• Periklis Mantenoglou
• Dimitrios Kelesis
• Alexander Artikis

Contemporary applications require the processing of large, high-velocity streams of symbolic events derived from sensor data. A complex event recognition (CER) system processes these symbolic events online and reports the satisfaction of complex event patterns with minimal latency. We extend an Event Calculus dialect optimised for online CER with Allen’s interval algebra, in order to provide more accurate event patterns. We demonstrate the effectiveness of our system on real data streams from maritime situational awareness.

IJCAI Conference 2023 Conference Paper

Incremental Event Calculus for Run-Time Reasoning (Extended Abstract)

• Efthimis Tsilionis
• Alexander Artikis
• Georgios Paliouras

We present a system for online, incremental composite event recognition. In streaming environments, the usual case is for data to arrive with a (variable) delay from, and to be revised by, the underlying sources. We propose RTEC_inc, an incremental version of RTEC, a composite event recognition engine with formal, declarative semantics, that has been shown to scale to several real-world data streams. RTEC deals with delayed arrival and revision of events by computing all queries from scratch. This is often inefficient since it results in redundant computations. Instead, RTEC_inc deals with delays and revisions in a more efficient way, by updating only the affected queries. We compare RTEC_inc and RTEC experimentally using real-world and synthetic datasets. The results are compatible with our complexity analysis and show that RTEC_inc outperforms RTEC in many practical cases.

JAIR Journal 2022 Journal Article

Incremental Event Calculus for Run-Time Reasoning

• Efthimis Tsilionis
• Alexander Artikis
• Georgios Paliouras

We present a system for online, incremental composite event recognition. In streaming environments, the usual case is for data to arrive with a (variable) delay from, and to be revised by, the underlying sources. We propose RTECinc, an incremental version of RTEC, a composite event recognition engine with formal, declarative semantics, that has been shown to scale to several real-world data streams. RTEC deals with delayed arrival and revision of events by computing all queries from scratch. This is often inefficient since it results in redundant computations. Instead, RTECinc deals with delays and revisions in a more efficient way, by updating only the affected queries. We examine RTECinc theoretically, presenting a complexity analysis, and show the conditions in which it outperforms RTEC. Moreover, we compare RTECinc and RTEC experimentally using real-world and synthetic datasets. The results are compatible with our theoretical analysis and show that RTECinc outperforms RTEC in many practical cases.

KR Conference 2022 System Paper

Stream Reasoning with Cycles

• Periklis Mantenoglou
• Manolis Pitsikalis
• Alexander Artikis

Temporal specifications, such as those found in multi-agent systems, often include cyclic dependencies. Moreover, there is an increasing need to evaluate such specifications in an online manner, upon streaming data. Consider, for example, the online computation of the normative positions of the agents engaging in an e-commerce protocol. We present a formal computational framework that deals with cyclic dependencies in an efficient way. Moreover, we demonstrate the effectiveness of our framework on large synthetic and real data streams, from the fields of multi-agent systems and composite event recognition.

ECAI Conference 2020 Conference Paper

Online Probabilistic Interval-Based Event Calculus

• Periklis Mantenoglou
• Alexander Artikis
• Georgios Paliouras

Activity recognition systems detect temporal combinations of ‘low-level’ or ‘short-term’ activities on sensor data. These systems exhibit various types of uncertainty, often leading to erroneous detection. We present an extension of an interval-based activity recognition system which operates on top of a probabilistic Event Calculus implementation. Our proposed system performs online recognition, as opposed to batch processing, thus supporting data streams. The empirical analysis demonstrates the efficacy of our system, comparing it to interval-based batch recognition, point-based recognition, as well as structure and weight learning models.

KR Conference 2020 System Paper

WOLED: A tool for Online Learning Weighted Answer Set Rules for Temporal Reasoning Under Uncertainty

• Nikos Katzouris
• Alexander Artikis

Complex Event Recognition (CER) systems detect event occurrences in streaming time-stamped input using predefined event patterns. Logic-based approaches are of special interest in CER, since, via Statistical Relational AI, they combine uncertainty-resilient reasoning with time and change, with machine learning, thus alleviating the cost of manual event pattern authoring. We present WOLED, a system based on Answer Set Programming (ASP), capable of probabilistic reasoning with complex event patterns in the form of weighted rules in the Event Calculus, whose structure and weights are learnt online. We compare our ASP-based implementation with a Markov Logic-based one and with a crisp version of the algorithm that learns unweighted rules, on CER datasets for activity recognition, maritime surveillance and fleet management. Our results demonstrate the superiority of our novel implementation, both in terms of efficiency and predictive performance.

TIME Conference 2018 Conference Paper

A Stream Reasoning System for Maritime Monitoring

• Georgios M. Santipantakis
• Akrivi Vlachou
• Christos Doulkeridis
• Alexander Artikis
• Ioannis Kontopoulos
• George A. Vouros

We present a stream reasoning system for monitoring vessel activity in large geographical areas. The system ingests a compressed vessel position stream, and performs online spatio-temporal link discovery to calculate proximity relations between vessels, and topological relations between vessel and static areas. Capitalizing on the discovered relations, a complex activity recognition engine, based on the Event Calculus, performs continuous pattern matching to detect various types of dangerous, suspicious and potentially illegal vessel activity. We evaluate the performance of the system by means of real datasets including kinematic messages from vessels, and demonstrate the effects of the highly efficient spatio-temporal link discovery on performance.

LPAR Conference 2018 Conference Paper

Wayeb: a Tool for Complex Event Forecasting

• Elias Alevizos
• Alexander Artikis
• Georgios Paliouras

Complex Event Processing (CEP) systems have appeared in abundance during the last two decades. Their purpose is to detect in real–time interesting patterns upon a stream of events and to inform an analyst for the occurrence of such patterns in a timely manner. However, there is a lack of methods for forecasting when a pattern might occur before such an occurrence is actually detected by a CEP engine. We present Wayeb, a tool that attempts to address the issue of Complex Event Forecasting. Wayeb employs symbolic automata as a computational model for pattern detection and Markov chains for deriving a probabilistic description of a symbolic automaton.

AILAW Journal 2015 Journal Article

The open agent society: retrospective and prospective views

• Jeremy Pitt
• Alexander Artikis

Abstract It is now more than ten years since the EU FET project ALFEBIITE finished, during which its researchers made original and distinctive contributions to ( inter alia ) formal models of trust, model-checking, and action logics. ALFEBIITE was also a highly inter-disciplinary project, with partners from computer science, philosophy, cognitive science and law. In this paper, we reflect on the interaction between computer scientists and information and IT lawyers on the idea of the ‘open agent society’. This inspired a programme of research whose investigation into conceptual challenges has carried it from the logical specification of agent societies and dynamic norm-governed systems to self-organising electronic institutions, while developing several technologies for agent-based modelling and complex event recognition. The outcomes of this inter-disciplinary collaboration have also influenced current research into using the open agent society as a platform for socio-technical systems, and other collective adaptive systems. We present a number of research challenges, including the ideas of computational justice and polycentric governance, and explore a number of ethical, legal and social implications. We contend that, in order to address these issues and challenges, the continued inter-disciplinary collaboration between computer science and IT lawyers is critical.

TIST Journal 2013 Journal Article

Introduction to the special section on agent communication

• Amit K. Chopra
• Alexander Artikis
• Jamal Bentahar
• Frank Dignum

TIST Journal 2013 Journal Article

Research directions in agent communication

• Amit K. Chopra
• Alexander Artikis
• Jamal Bentahar
• Marco Colombetti
• Frank Dignum
• Nicoletta Fornara
• Andrew J. I. Jones
• Munindar P. Singh

Increasingly, software engineering involves open systems consisting of autonomous and heterogeneous participants or agents who carry out loosely coupled interactions. Accordingly, understanding and specifying communications among agents is a key concern. A focus on ways to formalize meaning distinguishes agent communication from traditional distributed computing: meaning provides a basis for flexible interactions and compliance checking. Over the years, a number of approaches have emerged with some essential and some irrelevant distinctions drawn among them. As agent abstractions gain increasing traction in the software engineering of open systems, it is important to resolve the irrelevant and highlight the essential distinctions, so that future research can be focused in the most productive directions. This article is an outcome of extensive discussions among agent communication researchers, aimed at taking stock of the field and at developing, criticizing, and refining their positions on specific approaches and future challenges. This article serves some important purposes, including identifying (1) points of broad consensus; (2) points where substantive differences remain; and (3) interesting directions of future work.

TAAS Journal 2012 Journal Article

Axiomatization of Socio-Economic Principles for Self-Organizing Institutions

• Jeremy Pitt
• Julia Schaumeier
• Alexander Artikis

We address the problem of engineering self-organizing electronic institutions for resource allocation in open, embedded, and resource-constrained systems. In such systems, there is decentralized control, competition for resources and an expectation of both intentional and unintentional errors. The “optimal” distribution of resources is then less important than the endurance of the distribution mechanism. Under these circumstances, we propose to model resource allocation as a common-pool resource management problem, and develop a formal characterization of Elinor Ostrom’s socio-economic principles for self-governing institutions. This article applies a method for sociologically inspired computing to give a complete axiomatization of six of Ostrom’s eight principles in the Event Calculus. A testbed is implemented for experimenting with the axiomatization. The experimental results show that these principles support enduring institutions, in terms of longevity and membership, and also provide insight into calibrating the transaction and running costs associated with implementing the principles against the behavioral profile of the institutional membership. We conclude that it is possible to express Ostrom’s principles in logical form and that they are necessary and sufficient conditions for enduring self-organizing electronic institutions to manage sustainable common-pool resources.

ECAI Conference 2012 Conference Paper

Event Processing for Intelligent Resource Management

• Alexander Artikis
• Robin Marterer
• Jens Pottebaum
• Georgios Paliouras

The need for intelligent resource management (IRM) spans across a multitude of applications. To address this requirement, we present EP-IRM, an event processing system recognising composite events given multiple sources of information in order to support IRM. EP-IRM has been deployed in two real-world applications. Moreover, with a small effort it may be used in a wide range of applications requiring IRM. We present an evaluation of the system, and discuss the lessons learnt during its development and deployment.

KER Journal 2012 Journal Article

Logic-based event recognition

• Alexander Artikis
• Anastasios Skarlatidis
• François Portet
• Georgios Paliouras

Abstract Today's organizations require techniques for automated transformation of their large data volumes into operational knowledge. This requirement may be addressed by using event recognition systems that detect events/activities of special significance within an organization, given streams of ‘low-level’ information that is very difficult to be utilized by humans. Consider, for example, the recognition of attacks on nodes of a computer network given the Transmission Control Protocol/Internet Protocol messages, the recognition of suspicious trader behaviour given the transactions in a financial market and the recognition of whale songs given a symbolic representation of whale sounds. Various event recognition systems have been proposed in the literature. Recognition systems with a logic-based representation of event structures, in particular, have been attracting considerable attention, because, among others, they exhibit a formal, declarative semantics, they have proven to be efficient and scalable and they are supported by machine learning tools automating the construction and refinement of event structures. In this paper, we review representative approaches of logic-based event recognition and discuss open research issues of this field. We illustrate the reviewed approaches with the use of a real-world case study: event recognition for city transport management.

KR Conference 2010 Conference Paper

Run-Time Services for Norm-Governed Systems

• Visara Urovi
• Stefano Bromuri
• Kostas Stathis
• Alexander Artikis

AIJ Journal 2007 Journal Article

An executable specification of a formal argumentation protocol

• Alexander Artikis
• Marek Sergot
• Jeremy Pitt

We present a specification, in the action language C +, of Brewka's reconstruction of a theory of formal disputation originally proposed by Rescher. The focus is on the procedural aspects rather than the adequacy of this particular protocol for the conduct of debate and the resolution of disputes. The specification is structured in three separate levels, covering (i) the physical capabilities of the participant agents, (ii) the rules defining the protocol itself, specifying which actions are ‘proper’ and ‘timely’ according to the protocol and their effects on the protocol state, and (iii) the permissions, prohibitions, and obligations of the agents, and the sanctions and enforcement strategies that deal with non-compliance. Also included is a mechanism by which an agent may object to an action by another participant, and an optional ‘silence implies consent’ principle. Although comparatively simple, Brewka's protocol is thus representative of a wide range of other more complex argumentation and dispute resolution procedures that have been proposed. Finally, we show how the ‘Causal Calculator’ implementation of C + can be used to animate the specification and to investigate and verify properties of the protocol.

AAMAS Conference 2005 Conference Paper

Formalization of a Voting Protocol for Virtual Organizations

• Jeremy Pitt
• Lloyd Kamara
• Marek Sergot
• Alexander Artikis

AAMAS Conference 2002 Conference Paper

Animated Specification of Computational Societies.

• Alexander Artikis
• Jeremy Pitt
• Marek Sergot