Protocols with Exceptions, Timeouts, and Handlers: A Uniform Framework for Monitoring Fail-Uncontrolled and Ambient Intelligence Systems

This paper describes an approach for designing, formalizing and implementing sentinels that detect errors in fail-uncontrolled multiagent systems, and controllers that identify particular situations in ambient intelligence (AmI) systems. The formalism we use for representing the expected patterns of actions along with exceptions, timeouts, and their handlers, is that of constrained global types extended with features for dealing with these new constructs. We provide the syntax and semantics of the extended constrained global types and examples of their use, in the different contexts of fail-uncontrolled and AmI systems.

[1]  Hani Hagras,et al.  Creating an ambient-intelligence environment using embedded agents , 2004, IEEE Intelligent Systems.

[2]  Kathrin Abendroth.  Delta 4 A Generic Architecture For Dependable Distributed Computing , 2016 .

[3]  Mikal Ziane,et al.  Monitoring and organizational-level adaptation of multi-agent systems , 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

[4]  Hani Hagras,et al.  An Intelligent Fuzzy Agent Approach for Realising Ambient Intelligence in Intelligent Inhabited Environments , 2005 .

[5]  Michael C. Mozer,et al.  The Neural Network House: An Environment that Adapts to its Inhabitants , 1998 .

[6]  Davide Ancona,et al.  Attribute Global Types for Dynamic Checking of Protocols in Logic-based Multiagent Systems , 2013, Theory Pract. Log. Program..

[7]  Davide Ancona,et al.  Automatic Generation of Self-monitoring MASs from Multiparty Global Session Types in Jason , 2012, DALT.

[8]  Fred Kröger,et al.  Temporal Logic of Programs , 1987, EATCS Monographs on Theoretical Computer Science.

[9]  Winfried Lamersdorf,et al.  Augmenting BDI Agents with Deliberative Planning Techniques , 2006, PROMAS.

[10]  Yves Demazeau,et al.  FROM INTERACTIONS TO COLLECTIVE BEHAVIOUR IN AGENT-BASED SYSTEMS , 1995 .

[11]  Michael Wooldridge,et al.  Programming Multi-Agent Systems in AgentSpeak using Jason (Wiley Series in Agent Technology) , 2007 .

[12]  Paul Davidsson,et al.  Saving Energy and Providing Value Added Services in Intelligent Buildings: A MAS Approach , 2000, ASA/MA.

[13]  Davide Ancona,et al.  Efficient Verification of MASs with Projections , 2014, EMAS@AAMAS.

[14]  Juan Carlos Augusto,et al.  Ambient Intelligence—the Next Step for Artificial Intelligence , 2008, IEEE Intelligent Systems.

[15]  Angelo Ferrando,et al.  Global Protocols as First Class Entities for Self-Adaptive Agents , 2015, AAMAS.

[16]  Jamal Bentahar,et al.  On the interaction between knowledge and social commitments in multi-agent systems , 2014, Applied Intelligence.

[17]  Staffan Haegg,et al.  A Sentinel Approach to Fault Handling in Multi-Agent Systems , 1996, DAI.

[18]  Andrei Olaru.  Context-Awareness in Multi-agent Systems for Ambient Intelligence , 2014, Context in Computing.

[19]  Guido Boella,et al.  AI*IA 2013: Advances in Artificial Intelligence , 2013, Lecture Notes in Computer Science.

[20]  Davide Ancona,et al.  On the Expressiveness of Attribute Global Types: The Formalization of a Real Multiagent System Protocol , 2013, AI*IA.

[21]  Djamel-Eddine Saïdouni,et al.  A Higher-order Agent Model with Contextual Management for Ambient Systems , 2016 .

[22]  Davide Ancona,et al.  Constrained global types for dynamic checking of protocol conformance in multi-agent systems , 2013, SAC '13.

[23]  Eugenio Di Sciascio,et al.  Semantic-Based Resource Discovery and Orchestration in Home and Building Automation: A Multi-Agent Approach , 2014, IEEE Transactions on Industrial Informatics.

[24]  Gery Gutnik,et al.  Monitoring large-scale multi-agent systems using overhearing , 2005, AAMAS '05.

[25]  James Harland,et al.  Checking consistency of agent designs against interaction protocols for early-phase defect location , 2014, AAMAS.

[26]  Mark S. Fox,et al.  COOL: A Language for Describing Coordination in Multi Agent Systems , 1995, ICMAS.

[27]  Michael H. Coen,et al.  Design Principles for Intelligent Environments , 1998, AAAI/IAAI.

[28]  Cristina Baroglio,et al.  Typing Multi-Agent Systems via Commitments , 2014, EMAS@AAMAS.

[29]  Rafael H. Bordini,et al.  Applying Ontologies and Agent Technologies to Generate Ambient Intelligence Applications , 2014, ARE/AVSA@AAMAS.

[30]  Antonio Fernández-Caballero,et al.  IDK and ICARO to develop multi-agent systems in support of Ambient Intelligence , 2015, J. Intell. Fuzzy Syst..

[31]  Agostino Poggi,et al.  Developing Multi-agent Systems with JADE , 2007, ATAL.

[32]  Munindar P. Singh,et al.  Modeling exceptions via commitment protocols , 2005, AAMAS '05.

[33]  Davide Ancona,et al.  Distributed Runtime Verification of JADE Multiagent Systems , 2014, IDC.

[34]  David Daza,et al.  Cooperative Learning Model based on Multi-Agent Architecture for Embedded Intelligent Systems , 2014 .

[35]  Salvatore Venticinque,et al.  Intelligent Distributed Computing VIII - Proceedings of the 8th International Symposium on Intelligent Distributed Computing, IDC 2014, Madrid, Spain, September 3-5, 2014 , 2015, IDC.

[36]  Munindar P. Singh,et al.  Reasoning about Commitments in the Event Calculus: An Approach for Specifying and Executing Protocols , 2004, Annals of Mathematics and Artificial Intelligence.

[37]  Olivier Marin,et al.  DimaX: a fault-tolerant multi-agent platform , 2006, SELMAS '06.

[38]  Johann Eder,et al.  The Workflow Activity Model WAMO , 1995, CoopIS.