The cognitive agents specification language and verification environment for multiagent systems

Shapiro, Steven D.; Lespérance, Yves; Levesque, Hector J.

doi:10.1145/544743.544746

Cited by 16 publications

(16 citation statements)

References 10 publications

(16 reference statements)

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“…Projection by regression in the presence of multiple agents has been addressed in the literature. For instance, the epistemic situation calculus [Scherl and Levesque, 2003] has been extended to the many agent case in earlier work [Shapiro et al, 2002]. Recently, Kelly and Pearce [2008] consider evaluating epistemic queries, including queries about common knowledge [Fagin et al, 1995], by means of a meta-level operator using regression.…”

Section: Discussionmentioning

confidence: 99%

“…While there have been proposals to expand the vocabulary of the situation calculus for representing knowledge [Moore, 1985a;Scherl and Levesque, 2003], even in the multiagent case [Shapiro et al, 2002], we argued that simply dealing with a set of sentences that an agent supposedly believes does not quite capture what we intuitively understand by a knowledge base. A knowledge base, in our view, should be all that an agent knows.…”

Section: The Approachmentioning

confidence: 95%

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On the projection problem in active knowledge bases with incomplete information

Belle

2014

AI Matters

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The problem of projection has been identified as a fundamental reasoning concern in dynamical domains, where we are to determine whether or not some conditions will hold after a sequence of actions has been performed starting in some initial state. Solving the problem requires, at the very least, effectively reasoning about how actions transform the world, and inferring the logical consequences of the initial knowledge base Completing this Ph.D. has been an enriching journey. What follows is my humble attempt to thank those who have been a part of this ride, through its many potholes. Let me begin by expressing my sincere gratitude to Professor Gerhard Lakemeyer, for first encouraging me to find my own path, and then offering valuable suggestions to realize my goals. My previous background was in machine learning, and I imagine my initial intuitions about epistemic logic must have seemed peculiar. In spite of that, Gerhard patiently helped me fix my technical knowledge, allowed me to explore tangential ideas freely, and more importantly, shared his thoughts on what makes a problem interesting. He has overseen my academic growth for the past four years, and his views on mathematical logic and artificial intelligence have greatly influenced my own. For all of this, for showing me how to write scientifically, and for your continued guidance and support: thank you. A special thanks also goes to my external examiner Professor Hector Levesque for painstakingly reading this thesis, and bringing significant bugs and typographical errors to my attention. Carrying out my work at the Knowledge-based Systems Group has been a lot of fun. I thank its members for great corridor and coffee conversations. Participating in soccer matches, and doctoral seminar escapes to picturesque countrysides, with the remainder of Informatik 5 was very exciting, and I hope these traditions are here to stay. I also thank Jens Claßen for technical discussions, and Tim Niemüller for offering to translate the abstract of this thesis. A number of people visited the department over the years, and among them, I would especially like to thank Yongmei Liu for insightful conversations on research. She also had shared her intuitions about "forgetting" with me, which prompted me to explore that topic. I thank her for this. Financial support for the years 2008-2010 was gratefully received by the Deutsche Forschungsgemeinschaft (German Research Foundation), which funded the graduate school Software for mobile communication systems, of which I was a stipendiary. During my time at the graduate school, Prof. Otto Spaniol provided constant encouragement, and supported our participation in Dagstuhl seminars. For this, I am thankful. Further, Prof. Wolfgang Thomas encouraged me to present my results to the AlgoSyn graduate school, and for this, I thank Wolfgang. For much of the year 2011, financial support was received by the BIT research school, and for this I express my gratitude to Gerhard and Prof. Matthias Jarke. For the remainder of 2011, financial support w...

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Section: Discussionmentioning

confidence: 99%

Section: The Approachmentioning

confidence: 95%

On the projection problem in active knowledge bases with incomplete information

Belle

2014

AI Matters

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“…The Cognitive Agent Specification Language (CASL) was developed by Shapiro et al [5] to specify multiagent systems. The CASL views agents as entities that consist of mental states.…”

Section: Related Workmentioning

confidence: 99%

“…The expressiveness of CASL [5] is limited due to the modeling notations used. Also, CASL is difficult use with complex multiagent systems.…”

Section: Comparison With Related Workmentioning

confidence: 99%

A formal specification language for modeling agent systems

Subburaj

Urban

2013

2013 Second International Conference on Informatics &Amp; Applications (ICIA)

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Formal methods in software specification enable the development of reliable software with a reduction in magnitude of unidentified errors that might occur while developing software systems. The state of the practice with regards to formal methods in software specification, as well as in other phases of the software life cycle, is not clear and well defined since the field is still immature. This paper defines the need for applying formal methods while specifying and developing software systems. The Descartes specification language, a formal executable specification language, was taken into study to specify software systems. A description of agent oriented systems along with the extended constructs of the Descartes specification language for specifying agent systems was defined in this research. A concrete agent architecture with a generalized notation for formally specifying agent oriented systems was defined in this paper. The integration of formally specifying complex systems using agent oriented technology with the extended Descartes language constructs will impact the current ways of specifying software systems. Also, the paper can help bridge the gap between the specification, design, and the implementation phases of software development.

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“…However, ConGolog lacks mandatory communication predicates, in particular, it cannot explicitly express the internal mental state of agents (belief, intention, etc). Many theorists have done some significant work [7,8,9]. But their multi-agent system neglect the physical actions performed by agents for realizing their cooperation.…”

Section: Introductionmentioning

confidence: 99%

Cooperation Model of Multi-agent System Based on the Situation Calculus

Liu

Dong

Sun

2006

2006 IEEE/WIC/ACM International Conference on Intelligent Agent Technology

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In multi-agent system, the Requirement/Service is a cooperation way that is simple, efficient, and wildly applied. Under the framework of Situation Calculus, the agents' belief and intention are formalized, and some new communication actions are introduced into the earlier ConGolog. Consequently, we propose a Requirement/Service cooperative model and semantics for multi-agent System based on the extended ConGolog. What's more, in terms of the model and semantics, we specify a case of the multi-agent system in the dynamic and incompletely known environment for achieving the cooperation based on reason about action.

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The cognitive agents specification language and verification environment for multiagent systems

Cited by 16 publications

References 10 publications

On the projection problem in active knowledge bases with incomplete information

On the projection problem in active knowledge bases with incomplete information

A formal specification language for modeling agent systems

Cooperation Model of Multi-agent System Based on the Situation Calculus

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