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

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

Verifying requirements for resource-bounded agents

This thesis presents frameworks for the modelling and verification of resource-bounded reasoning agents. The resources considered include the time, memory, and communication bandwidth required by agents to achieve a goal. The scalability and expressiveness of standard model checking techniques is investigated using two typical multiagent reasoning problems which can be easily parameterised to increase or decrease the problem size. Both a complexity analysis and experimental results suggest that reasonably sized problem instances are unlikely to be tractable for a standard model checker without steps to reduce the branching factor of the state space. We propose two approaches to address this problem: the use of abstract specifications to model the behaviour of some of the agents in the system, and exploiting information about the reasoning strategy adopted by the agents. Abstract specifications are given as Linear Temporal Logic (LTL) formulae which describe the external behaviour of the agents, allowing their temporal behaviour to be compactly modelled. Conversely, reasoning strategies allow the detailed specification of the ordering of steps in the agent’s reasoning process. Both approaches have been combined in an automated verification tool TVRBA for rule-based multi-agent systems which allows the designer to specify information about agents’ interaction, behaviour, and execution strategy at different levels of abstraction. The TVRBA tool generates an encoding of the system for the Maude LTL model checker, allowing properties of the system to be verified. The scalability of the new approach is illustrated using three case studies

Rational Agents: Prioritized Goals, Goal Dynamics, and Agent Programming Languages with Declarative Goals

I introduce a specification language for modeling an agent's prioritized goals and their dynamics. I use the situation calculus along with Reiter's solution to the frame problem and predicates for describing agents' knowledge as my base formalism. I further enhance this language by introducing a new sort of infinite paths. Within this language, I discuss how to systematically specify prioritized goals and how to precisely describe the effects of actions on these goals. These actions include adoption and dropping of goals and subgoals. In this framework, an agent's intentions are formally specified as the prioritized intersection of her goals. The ``prioritized'' qualifier above means that the specification must respect the priority ordering of goals when choosing between two incompatible goals. I ensure that the agent's intentions are always consistent with each other and with her knowledge. I investigate two variants with different commitment strategies. Agents specified using the ``optimizing'' agent framework always try to optimize their intentions, while those specified in the ``committed'' agent framework will stick to their intentions even if opportunities to commit to higher priority goals arise when these goals are incompatible with their current intentions. For these, I study properties of prioritized goals and goal change. I also give a definition of subgoals, and prove properties about the goal-subgoal relationship. As an application, I develop a model for a Simple Rational Agent Programming Language (SR-APL) with declarative goals. SR-APL is based on the ``committed agent'' variant of this rich theory, and combines elements from Belief-Desire-Intention (BDI) APLs and the situation calculus based ConGolog APL. Thus SR-APL supports prioritized goals and is grounded on a formal theory of goal change. It ensures that the agent's declarative goals and adopted plans are consistent with each other and with her knowledge. In doing this, I try to bridge the gap between agent theories and practical agent programming languages by providing a model and specification of an idealized BDI agent whose behavior is closer to what a rational agent does. I show that agents programmed in SR-APL satisfy some key rationality requirements

A platform-independent domain-specific modeling language for multiagent systems

Associated with the increasing acceptance of agent-based computing as a novel software engineering paradigm, recently a lot of research addresses the development of suitable techniques to support the agent-oriented software development. The state-of-the-art in agent-based software development is to (i) design the agent systems basing on an agent-based methodology and (ii) take the resulting design artifact as a base to manually implement the agent system using existing agent-oriented programming languages or general purpose languages like Java. Apart from failures made when manually transform an abstract specification into a concrete implementation, the gap between design and implementation may also result in the divergence of design and implementation. The framework discussed in this dissertation presents a platform-independent domain-specific modeling language for MASs called Dsml4MAS that allows modeling agent systems in a platform-independent and graphical manner. Apart from the abstract design, Dsml4MAS also allows to automatically (i) check the generated design artifacts against a formal semantic specification to guarantee the well-formedness of the design and (ii) translate the abstract specification into a concrete implementation. Taking both together, Dsml4MAS ensures that for any well-formed design, an associated implementation will be generated closing the gap between design and code.Aufgrund wachsender Akzeptanz von Agentensystemen zur Behandlung komplexer Problemstellungen wird der Schwerpunkt auf dem Gebiet der agentenorientierten Softwareentwicklung vor allem auf die Erforschung von geeignetem Entwicklungswerkzeugen gesetzt. Stand der Forschung ist es dabei das Agentendesign mittels einer Agentenmethodologie zu spezifizieren und die resultierenden Artefakte als Grundlage zur manuellen Programmierung zu verwenden. Fehler, die bei dieser manuellen Überführung entstehen, machen insbesondere das abstrakte Design weniger nützlich in Hinsicht auf die Nachhaltigkeit der entwickelten Softwareapplikation. Das in dieser Dissertation diskutierte Rahmenwerk erörtert eine plattformunabhängige domänenspezifische Modellierungssprache für Multiagentensysteme namens Dsml4MAS. Dsml4MAS erlaubt es Agentensysteme auf eine plattformunabhängige und graphische Art und Weise darzustellen. Die Modellierungssprache umfasst (i) eine abstrakte Syntax, die das Vokabular der Sprache definiert, (ii) eine konkrete Syntax, die die graphische Darstellung spezifiziert sowie (iii) eine formale Semantik, die dem Vokabular eine präzise Bedeutung gibt. Dsml4MAS ist Bestandteil einer (semi-automatischen) Methodologie, die es (i) erlaubt die abstrakte Spezifikation schrittweise bis hin zur konkreten Implementierung zu konkretisieren und (ii) die Interoperabilität zu alternativen Softwareparadigmen wie z.B. Dienstorientierte Architekturen zu gewährleisten