Logic-Based Specification Languages for Intelligent Software Agents

The research field of Agent-Oriented Software Engineering (AOSE) aims to find abstractions, languages, methodologies and toolkits for modeling, verifying, validating and prototyping complex applications conceptualized as Multiagent Systems (MASs). A very lively research sub-field studies how formal methods can be used for AOSE. This paper presents a detailed survey of six logic-based executable agent specification languages that have been chosen for their potential to be integrated in our ARPEGGIO project, an open framework for specifying and prototyping a MAS. The six languages are ConGoLog, Agent-0, the IMPACT agent programming language, DyLog, Concurrent METATEM and Ehhf. For each executable language, the logic foundations are described and an example of use is shown. A comparison of the six languages and a survey of similar approaches complete the paper, together with considerations of the advantages of using logic-based languages in MAS modeling and prototyping.Comment: 67 pages, 1 table, 1 figure. Accepted for publication by the Journal "Theory and Practice of Logic Programming", volume 4, Maurice Bruynooghe Editor-in-Chie

Programming in logic without logic programming

In previous work, we proposed a logic-based framework in which computation is the execution of actions in an attempt to make reactive rules of the form if antecedent then consequent true in a canonical model of a logic program determined by an initial state, sequence of events, and the resulting sequence of subsequent states. In this model-theoretic semantics, reactive rules are the driving force, and logic programs play only a supporting role. In the canonical model, states, actions and other events are represented with timestamps. But in the operational semantics, for the sake of efficiency, timestamps are omitted and only the current state is maintained. State transitions are performed reactively by executing actions to make the consequents of rules true whenever the antecedents become true. This operational semantics is sound, but incomplete. It cannot make reactive rules true by preventing their antecedents from becoming true, or by proactively making their consequents true before their antecedents become true. In this paper, we characterize the notion of reactive model, and prove that the operational semantics can generate all and only such models. In order to focus on the main issues, we omit the logic programming component of the framework.Comment: Under consideration in Theory and Practice of Logic Programming (TPLP

Logic-based Technologies for Multi-agent Systems: A Systematic Literature Review

Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified with the whole AI by many non-computerscientists and non-technical media, symbolic approaches are getting more and more attention as those that could make AI amenable to human understanding. Given the recurring cycles in the AI history, we expect that a revamp of technologies often tagged as “classical AI” – in particular, logic-based ones will take place in the next few years. On the other hand, agents and multi-agent systems (MAS) have been at the core of the design of intelligent systems since their very beginning, and their long-term connection with logic-based technologies, which characterised their early days, might open new ways to engineer explainable intelligent systems. This is why understanding the current status of logic-based technologies for MAS is nowadays of paramount importance. Accordingly, this paper aims at providing a comprehensive view of those technologies by making them the subject of a systematic literature review (SLR). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones

A survey of agent-oriented methodologies

This article introduces the current agent-oriented methodologies. It discusses what approaches have been followed (mainly extending existing object oriented and knowledge engineering methodologies), the suitability of these approaches for agent modelling, and some conclusions drawn from the survey

Adding Organizations and Roles as Primitives to the JADE Framework

The organization metaphor is often used in the design and implementation of multiagent systems. However, few agent programming languages provide facilities to define them. Several frameworks are proposed to coordinate MAS with organizations, but they are not programmable with general purpose languages. In this paper we extend the JADE framework with primitives to program in Java organizations structured in roles and to enable agents to play roles in organizations. Roles facilitate the coordination of agents inside an organization and give new abilities in the context of organizations, called powers, to the agents which satisfy the requirements necessary to play the roles. As primitives to program organizations and roles we provide classes and protocols which enable an agent to enact a new role in an organization and to interact with the role by invoking the execution of powers, and to receive new goals to be fulfilled. Roles have state and behaviour, thus, they are instances of classes and are strictly connected with the organization offering them. Since roles and organizations can be on a different platform with respect to the role player, the communication with them happens via protocols. Moreover, since, besides using protocols, roles and organizations can have complex behaviours, they are implemented by extending the JADE agent class

A Roadmap to Pervasive Systems Verification

yesThe complexity of pervasive systems arises from the many different aspects that such systems possess. A typical pervasive system may be autonomous, distributed, concurrent and context-based, and may involve humans and robotic devices working together. If we wish to formally verify the behaviour of such systems, the formal methods for pervasive systems will surely also be complex. In this paper, we move towards being able to formally verify pervasive systems and outline our approach wherein we distinguish four distinct dimensions within pervasive system behaviour and utilise different, but appropriate, formal techniques for verifying each one.EPSR

Programming Service Oriented Agents

This paper introduces a programming language for service-oriented agents. JADL++ combines the ease of use of scripting-languages with a state-of-the-art service oriented approach which allows the seamless integration of web-services. Furthermore, the language includes OWL-based ontologies for semantic descriptions of data and services, thus allowing agents to make intelligent decisions about service calls

Système d'aide à la décision pour le réseau de distribution

RÉSUMÉ De nos jours, de nouvelles technologies issues du domaine de l'information et de la communication sont introduites progressivement dans les réseaux de distribution électrique. Ces technologies nécessitent des études poussées et des simulations précises afin d'en évaluer les forces et les faiblesses. Toutefois, la simulation des réseaux électriques demeure une tâche complexe qui nécessite de tenir compte de plusieurs facteurs : électriques, mécaniques, économiques, naturels, matériels et humains. Pour pallier à la complexité inhérente à la simulation électrique, il est possible de recourir aux systèmes multiagents (SMA). Ils présentent de nombreux avantages. Ils offrent une grande flexibilité en permettant à des agents autonomes de collaborer pour atteindre des objectifs complexes. Le SMA, par opposition au système de simulation monolithique, présente l'avantage d'être une architecture souple et évolutive capable de traiter des opérations complexes. Toutefois, le développement et la manipulation de ces systèmes sont des tâches réservées à des experts en informatique et en SMA. Or, dans le cadre du projet LEOPAR, mené à l'Institut de recherche d'Hydro Québec, nous avons comme principal objectif de développer un SMA accessible à des non-experts en informatique. Le but est de permettre aux décideurs et aux ingénieurs électriques de modifier et de faire évoluer le simulateur de la manière la plus aisée possible. Pour ce faire, nous avons développée une architecture à mi-chemin entre les architectures de Tableau Noir et les SMA. Nous avons utilisé une zone distribuée de partage de données pour permettre la communication des agents. Le partage et l'échange d'informations se fait par la modification des données distribuées. Ce mécanisme réduit la complexité des agents et leur mode de communication. De plus, nous avons spécifié un langage d'actions de haut niveau qui permet de décrire de manière déclarative les actions, leurs effets, leurs conditions et leurs relations. Ce langage d'actions est automatiquement traduit en logique non monotone (Answer Set Programming) afin de permettre la coordination des agents du simulateur. La traduction que nous proposons du langage d'actions surpasse largement les autres langages d'actions en termes de rapidité d'exécution lors de la planification. La combinaison de notre langage d'actions et de la logique non monotone a permis le développement d'un système performant, qui offre la possibilité à des novices de rajouter, modifier ou supprimer des agents du simulateur. Le simulateur multiagents que nous avons développé fonctionne adéquatement et permet, entre autre, de réaliser des simulations de type Monte-Carlo pour l’étude de la fiabilité des réseaux. Notre simulateur permet de quantifier, à l'aide des indices de performances, l'impact et l'apport de nouvelles technologies. Il est en mesure de reproduire avec une grande fidélité des phénomènes électriques, mécaniques et humains, tels que la surcharge électrique des câbles, le changeur de prise des transformateurs, les équipes humaines d'intervention, le temps de restauration variable et la reconfiguration du réseau. Notre simulateur a été testé sur de véritables réseaux de distribution d'Hydro-Québec et a démontré sa capacité à traiter de grandes quantités de données. En comparaison à d'autres simulateurs électriques multiagents standards, notre système s'est avéré être tout aussi performant mais beaucoup plus facile à développer et à faire évoluer. Lors des simulations électriques, nous avons été en mesure de réaliser des études de fiabilité qui ont permis de déterminer les facteurs les plus importants influant les performances du réseau.----------ABSTRACT Nowadays, the information system technologies are increasingly used in power distribution systems to improve network reliability and performance. The impact of these structural changes is important and requires in-depth studies and investigations. A better understanding of the effect of these technologies is required to optimize the network. However, the simulation of power network is a complex task, where several technical issues need to be considered such as : electrical, mechanical, economical, natural and human aspects. The idea is to develop a multi-agent system (MAS) that can process complex simulations. Such a system is extensible and modular and it is composed by numerous simple agents that can collaborate and interact in order to achieve complex objectives. Multi-agent systems are capable of reaching goals that are difficult to achieve by monolithic systems or individual agents, which can be complex and hard to maintain and extend. Nevertheless, the development and the maintenance of a MAS is a complex task that has to be performed by experts on computer science and multi-agent systems. In the framework of the project LEOPAR, carried out by the \textit{Institute de Recherche d'Hydro-Québec}, we have as a main objective to develop an accessible and comprehensive MAS. The project's aim was to allow managers to modify the behavior and the objectives of the simulator without the assistance of an expert. To this end, we developed a simulator based on Blackboard and MAS. Our system relies on a common pool of data to share information between agents. This type of mechanism reduces the communication complexity and makes the development of agents easier. In addition, we defined a new action language that allows to incrementally describe the agent's actions, effects, conditions and relations. Our action language is automatically translated into a non-monotonic logic (Answer Set Programming) in order to process the agent's actions. The translated answer set program has shown to be effective in providing action plans. The action language combined to answer set programming allowed us to develop a powerful and accessible simulator, enabling novice to add, change, and remove agents' behavior. Our simulator works properly and allows, among other things, processing power network assessments using a Monte-Carlo approach. It analyses the impact of introducing new types of technologies, by comparing performance indicators of the network. Moreover, it is able to simulate with accuracy a wide variety of phenomena as wire overloading, protection mechanism activation, tap changer changes, human intervening team patrols, restoration process and network reconfiguration. It has been tested on realistic distribution network of Hydro-Quebec and it performed well in assessing networks. Our simulator is performing similarly to a classical multi-agents system, but with the benefit of being accessible and easy to use