An executable Theory of Multi-Agent Systems Refinement

Complex applications such as incident management, social simulations, manufacturing applications, electronic auctions, e-institutions, and business to business applications are pervasive and important nowadays. Agent-oriented methodology is an advance in abstractionwhich can be used by software developers to naturally model and develop systems for suchapplications. In general, with respect to design methodologies, what it may be important tostress is that control structures should be added at later stages of design, in a natural top-downmanner going from specifications to implementations, by refinement. Too much detail (be itfor the sake of efficiency) in specifications often turns out to be harmful. To paraphrase D.E.Knuth, “Premature optimization is the root of all evil” (quoted in ‘The Unix ProgrammingEnvironment’ by Kernighan and Pine, p. 91).The aim of this thesis is to adapt formal techniques to the agent-oriented methodologyinto an executable theory of refinement. The justification for doing so is to provide correctagent-based software by design. The underlying logical framework of the theory we proposeis based on rewriting logic, thus the theory is executable in the same sense as rewriting logicis. The storyline is as follows. We first motivate and explain constituting elements of agentlanguages chosen to represent both abstract and concrete levels of design. We then proposea definition of refinement between agents written in such languages. This notion of refinement ensures that concrete agents are correct with respect to the abstract ones. The advantageof the definition is that it easily leads to formulating a proof technique for refinement viathe classical notion of simulation. This makes it possible to effectively verify refinement bymodel-checking. Additionally, we propose a weakest precondition calculus as a deductivemethod based on assertions which allow to prove correctness of infinite state agents. Wegeneralise the refinement relation from single agents to multi-agent systems in order to ensure that concrete multi-agent systems refine their abstractions. We see multi-agent systemsas collections of coordinated agents, and we consider coordination artefacts as being basedeither on actions or on normative rules. We integrate these two orthogonal coordinationmechanisms within the same refinement theory extended to a timed framework. Finally, wediscuss implementation aspects.LEI Universiteit LeidenFoundations of Software Technolog

An executable theory of multi-agent systems refinement

Complex applications such as incident management, social simulations, manufacturing applications, electronic auctions, e-institutions, and business to business applications are pervasive and important nowadays. Agent-oriented methodology is an advance in abstractionwhich can be used by software developers to naturally model and develop systems for suchapplications. In general, with respect to design methodologies, what it may be important tostress is that control structures should be added at later stages of design, in a natural top-downmanner going from specifications to implementations, by refinement. Too much detail (be itfor the sake of efficiency) in specifications often turns out to be harmful. To paraphrase D.E.Knuth, “Premature optimization is the root of all evil” (quoted in ‘The Unix ProgrammingEnvironment’ by Kernighan and Pine, p. 91).The aim of this thesis is to adapt formal techniques to the agent-oriented methodologyinto an executable theory of refinement. The justification for doing so is to provide correctagent-based software by design. The underlying logical framework of the theory we proposeis based on rewriting logic, thus the theory is executable in the same sense as rewriting logicis. The storyline is as follows. We first motivate and explain constituting elements of agentlanguages chosen to represent both abstract and concrete levels of design. We then proposea definition of refinement between agents written in such languages. This notion of refinement ensures that concrete agents are correct with respect to the abstract ones. The advantageof the definition is that it easily leads to formulating a proof technique for refinement viathe classical notion of simulation. This makes it possible to effectively verify refinement bymodel-checking. Additionally, we propose a weakest precondition calculus as a deductivemethod based on assertions which allow to prove correctness of infinite state agents. Wegeneralise the refinement relation from single agents to multi-agent systems in order to ensure that concrete multi-agent systems refine their abstractions. We see multi-agent systemsas collections of coordinated agents, and we consider coordination artefacts as being basedeither on actions or on normative rules. We integrate these two orthogonal coordinationmechanisms within the same refinement theory extended to a timed framework. Finally, wediscuss implementation aspects.LEI Universiteit LeidenFoundations of Software Technolog

Hierarchical agent supervision

Agent supervision is a form of control/customization where a supervisor restricts the behavior of an agent to enforce certain requirements, while leaving the agent as much autonomy as possible. To facilitate supervision, it is often of interest to consider hierarchical models where a high level abstracts over low-level behavior details. We study hierarchical agent supervision in the context of the situation calculus and the ConGolog agent programming language, where we have a rich first-order representation of the agent state. We define the constraints that ensure that the controllability of in-dividual actions at the high level in fact captures the controllability of their implementation at the low level. On the basis of this, we show that we can obtain the maximally permissive supervisor by first considering only the high-level model and obtaining a high- level supervisor and then refining its actions locally, thus greatly simplifying the supervisor synthesis task

Abstraction of Agents Executing Online and their Abilities in the Situation Calculus

We develop a general framework for abstracting online behavior of an agent that may acquire new knowledge during execution (e.g., by sensing), in the situation calculus and ConGolog. We assume that we have both a high-level action theory and a low-level one that represent the agent's behavior at different levels of detail. In this setting, we define ability to perform a task/achieve a goal, and then show that under some reasonable assumptions, if the agent has a strategy by which she is able to achieve a goal at the high level, then we can refine it into a low-level strategy to do so

Abstraction in situation calculus action theories

We develop a general framework for agent abstraction based on the situation calculus and the ConGolog agent programming language. We assume that we have a high-level specification and a low-level specification of the agent, both repre- sented as basic action theories. A refinement mapping specifies how each high-level action is implemented by a low- level ConGolog program and how each high-level fluent can be translated into a low-level formula. We define a notion of sound abstraction between such action theories in terms of the existence of a suitable bisimulation between their respective models. Sound abstractions have many useful properties that ensure that we can reason about the agent’s actions (e.g., executability, projection, and planning) at the abstract level, and refine and concretely execute them at the low level. We also characterize the notion of complete abstraction where all actions (including exogenous ones) that the high level thinks can happen can in fact occur at the low level

Abstraction in situation calculus action theories

We develop a general framework for agent abstraction based on the situation calculus and the ConGolog agent programming language. We assume that we have a high-level specification and a low-level specification of the agent, both repre- sented as basic action theories. A refinement mapping specifies how each high-level action is implemented by a low- level ConGolog program and how each high-level fluent can be translated into a low-level formula. We define a notion of sound abstraction between such action theories in terms of the existence of a suitable bisimulation between their respective models. Sound abstractions have many useful properties that ensure that we can reason about the agent’s actions (e.g., executability, projection, and planning) at the abstract level, and refine and concretely execute them at the low level. We also characterize the notion of complete abstraction where all actions (including exogenous ones) that the high level thinks can happen can in fact occur at the low level

Metamodel-based model conformance and multiview consistency checking

Model-driven development, using languages such as UML and BON, often makes use of multiple diagrams (e.g., class and sequence diagrams) when modeling systems. These diagrams, presenting different views of a system of interest, may be inconsistent. A metamodel provides a unifying framework in which to ensure and check consistency, while at the same time providing the means to distinguish between valid and invalid models, that is, conformance. Two formal specifications of the metamodel for an object-oriented modeling language are presented, and it is shown how to use these specifications for model conformance and multiview consistency checking. Comparisons are made in terms of completeness and the level of automation each provide for checking multiview consistency and model conformance. The lessons learned from applying formal techniques to the problems of metamodeling, model conformance, and multiview consistency checking are summarized

A formal foundation for ontology alignment interaction models

Ontology alignment foundations are hard to find in the literature. The abstract nature of the topic and the diverse means of practice makes it difficult to capture it in a universal formal foundation. We argue that such a lack of formality hinders further development and convergence of practices, and in particular, prevents us from achieving greater levels of automation. In this article we present a formal foundation for ontology alignment that is based on interaction models between heterogeneous agents on the Semantic Web. We use the mathematical notion of information flow in a distributed system to ground our three hypotheses of enabling semantic interoperability and we use a motivating example throughout the article: how to progressively align two ontologies of research quality assessment through meaning coordination. We conclude the article with the presentation---in an executable specification language---of such an ontology-alignment interaction model

Analysis of Dialogical Argumentation via Finite State Machines

Dialogical argumentation is an important cognitive activity by which agents exchange arguments and counterarguments as part of some process such as discussion, debate, persuasion and negotiation. Whilst numerous formal systems have been proposed, there is a lack of frameworks for implementing and evaluating these proposals. First-order executable logic has been proposed as a general framework for specifying and analysing dialogical argumentation. In this paper, we investigate how we can implement systems for dialogical argumentation using propositional executable logic. Our approach is to present and evaluate an algorithm that generates a finite state machine that reflects a propositional executable logic specification for a dialogical argumentation together with an initial state. We also consider how the finite state machines can be analysed, with the minimax strategy being used as an illustration of the kinds of empirical analysis that can be undertaken.Comment: 10 page