Compositional Verification of Multi-Agent Systems in Temporal Multi-Epistemic Logic

Engelfriet, Joeri; Jonker, Catholijn M.; Treur, Jan

doi:10.1007/978-94-017-1741-0_9

Cited by 13 publications

(10 citation statements)

References 11 publications

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“…al. [4] may prove useful here. In addition, we would like to handle recursive procedures in CASL using the framework of De Giacomo et.…”

Section: Discussionmentioning

confidence: 99%

“…A step here is either a primitive action or testing whether a condition holds in the current situation. They introduce two special predicates, FinalDG and TransDG, where 4 De Giacomo et. al.…”

Section: Agent Behaviormentioning

confidence: 99%

“…We have proven such a lemma and discuss it in detail in Sec. 4, as an example of what is involved in the process of verification and building a library for this purpose. We show part of the proof in Sec.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The cognitive agents specification language and verification environment for multiagent systems

Shapiro¹,

Lespérance²,

Levesque³

2002

Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems Part 1 - AAMAS '02

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The Cognitive Agents Specification Language (CASL) is a framework for specifying multiagent systems. It has a mix of declarative and procedural components to facilitate the specification and verification of complex multiagent systems. In this paper, we describe CASL and a verification environment (CASLve) for it based on the PVS verification system. We give an example of a multiagent meeting scheduler application specified with CASL. To illustrate the verification system, we discuss a proof we carried out in it, namely, that all bounded-loop CASL specifications terminate.

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“…al. [4] may prove useful here. In addition, we would like to handle recursive procedures in CASL using the framework of De Giacomo et.…”

Section: Discussionmentioning

confidence: 99%

Section: Agent Behaviormentioning

confidence: 99%

See 1 more Smart Citation

The cognitive agents specification language and verification environment for multiagent systems

Shapiro¹,

Lespérance²,

Levesque³

2002

Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems Part 1 - AAMAS '02

View full text Add to dashboard Cite

show abstract

“…One of these methods is worked out in a tool called Smodels, based on answer set programming; cf. [25]. Another method to determine the extensions of a default theory is by controlled or prioritised default reasoning.…”

Section: Default Logic For Model-based Refinement Of Partial Informationmentioning

confidence: 99%

Methods for model-based reasoning within agent-based Ambient Intelligence applications

Bosse

Both

Gerritsen

et al. 2012

Knowledge-Based Systems

Self Cite

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Abstract. Within agent-based Ambient Intelligence applications agents react to humans based on information obtained by sensoring and their knowledge about human functioning. Appropriate types of reactions depend on the extent to which an agent understands the human and is able to interpret the available information (which is often incomplete, and hence multi-interpretable) in order to create a more complete internal image of the environment, including humans. Such an understanding requires that the agent has knowledge to a certain depth about the human"s physiological and mental processes in the form of an explicitly represented model of the causal and dynamic relations describing these processes. In addition, given such a model representation, the agent needs reasoning methods to derive conclusions from the model and interpret the (partial) information available by sensoring. This paper presents the development of a toolbox that can be used by a modeller to design Ambient Intelligence applications. This toolbox contains a number of model-based reasoning methods and approaches to control such reasoning methods. Formal specifications in an executable temporal format are offered, which allows for simulation of reasoning processes and automated verification of the resulting reasoning traces in a dedicated software environment. A number of such simulation experiments and their formal analysis are described. The main contribution of this paper is that the reasoning methods in the toolbox have the possibility to reason using both quantitative and qualitative aspects in combination with a temporal dimension, and the possibility to perform focused reasoning based upon certain heuristic information.

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“…A more complete property to cover such cases is the following. To obtain a logical foundation for a temporal variant of the Closed World Assumption in such situations in the context of executable temporal logic, in [13] the notion of temporal completion was introduced, as a temporal variant of Clark's completion in logic programming.…”

Section: Properties Of Leads To Relationshipsmentioning

confidence: 99%

Model-Based Reasoning Methods within an Ambient Intelligent Agent Model

Bosse

Both

Gerritsen

et al.

Communications in Computer and Information Science

Self Cite

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Abstract. Ambient agents react on humans on the basis of their information obtained by sensoring and their knowledge about human functioning. Appropriate types of reactions depend on in how far an ambient agent understands the human. On the one hand, such an understanding requires that the agent has knowledge to a certain depth about the human's physiological and mental processes in the form of an explicitly represented model of the causal and dynamic relations describing these processes. On the other hand, given such a model representation, the agent needs reasoning methods to derive conclusions from the model and the information available by sensoring. This paper presents a number of such model-based reasoning methods. They have been formally specified in an executable temporal format, which allows for simulation of reasoning traces and automated verification in a dedicated software environment. A number of such simulation experiments and their formal analysis are described.

show abstract

Compositional Verification of Multi-Agent Systems in Temporal Multi-Epistemic Logic

Cited by 13 publications

References 11 publications

The cognitive agents specification language and verification environment for multiagent systems

The cognitive agents specification language and verification environment for multiagent systems

Methods for model-based reasoning within agent-based Ambient Intelligence applications

Model-Based Reasoning Methods within an Ambient Intelligent Agent Model

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