Coordination for Situated MAS: Towards an Event-driven Architecture

Coordination for Situated MAS:Towards an Event-driven Architecture

Andrea [email protected]

Stefano [email protected]

DISIAlma Mater Studiorum–Universita di Bologna

ModBE’13 / PNSE’13Universita di Milano – Bicocca

25 June 2013

Omicini, Mariani (DISI, Alma Mater) Coordination for Situated MAS Milano Bicocca, 25/6/2013 1 / 45

mailto:[email protected]


http://www.disi.unibo.it

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http://apice.unibo.it/xwiki/bin/view/Events/Modbe2013

http://apice.unibo.it/xwiki/bin/view/Events/Pnse2013

http://www.unimib.it/

Outline

1 Motivation

2 MAS as Event-driven Systems

3 Boundary & Coordination Artefacts

4 A Concrete Event-driven Architecture in TuCSoN

5 Perspectives


Motivation

Outline

1 Motivation




5 Perspectives


Motivation

Situatedness

Coupling with Environment

Today’s complex computational systems require strict coupling withthe environment

pervasive, adaptive, self-organising systems need to work as situatedsystems

A situated system should be able to

react to relevant changes in the environmentpossibly act over the environment appropriately and timely

Interaction

Interaction with the environment is then one of the main issue incomplex computational systems nowadays [Weyns et al., 2007]

More generally, interaction is the foremost source of complexity intoday computational systems [Goldin et al., 2006]


Motivation

Agency & MAS I

Agent-oriented computing

Agent-oriented abstractions and technologies provide a solid groundfor complex system modelling and engineering

For instance

meta-models like A&A [Omicini et al., 2008]middlewares like CArtAgO [Ricci et al., 2007], JADE[Bellifemine et al., 2007], TuCSoN [Omicini and Zambonelli, 1999]agent-oriented methodologies like Gaia [Zambonelli et al., 2003],PASSI [Cossentino et al., 2005] and SODA [Molesini et al., 2006]

already proved their effectiveness in dealing with the engineering ofcomplex software systems [Zambonelli and Omicini, 2004]


Motivation

Agency & MAS II

Reactiveness vs. Proactiveness

The reactive nature of situated systems does not cope well with theproactive nature of agency

In particular, the event-driven model pushed by situatedness does notmatch high-level agent-oriented programming model


Motivation

Goal of the Research I

The Problem

The above issues are typically faced with more articulated agentlanguages and architectures – like hybrid agents architectures – e.g.,[Hallenborg et al., 2007]

MAS increasing complexity in terms of size and number ofcomponents and events mandates for principled solutions

There is a need for well-founded SE theories and practices

Possibly at MAS level rather than at single-component level


Motivation

Goal of the Research II

An Architectural Approach

Accordingly, in this talk we sketch an event-driven architecture foragent middleware

Exploiting coordination abstractions for event handling

In particular

we discuss its abstract architectural featureswe describe a possible reification as a concrete architecture based onthe TuCSoN middleware for multi-agent system (MAS) coordination[TuCSoN, 2013]


MAS as Event-driven Systems

Outline

1 Motivation




5 Perspectives



Environment Events I

Environment activity can be most easily modelled in terms of(possibly unpredictable) events

As a result, environment interaction with computational systems canbe modelled in an event-driven way

Event handling is articulated in a number of stages, such as (atleast):

selection of potentially-relevant eventsperception of selected eventsdelivering of perceived events to designed componentselaboration of events by components



Environment Events II

Figure : Event-driven architectures fundamental stages for event-processing



Agent Events

MAS are open, so agents may be either not designed or notcontrollable by MAS engineers

Non-trivial agents may be intrinsically complex, either by design or asa result of a too-articulated individual history

As a result, also agent activity in an open MAS should be handled asan unpredictable source of events

Agents events

Both organisation and security issues require modelling agents, too, as(possibly unpredictable) event sources within MAS, to be possibly handledvia event-driven engineering techniques.


Boundary & Coordination Artefacts

Outline

1 Motivation




5 Perspectives



Artefacts I

Artefacts

agents and environment are the most suitable abstractions to handleactivities in a MAS

artefacts are the most suitable abstractions to encapsulate reactivebehaviours

encapsulating events handling in a complex MAS

according to the A&A meta-model



Artefacts II

Agents & Artefacts meta-model (A&A) [Omicini et al., 2008]

Agents are

active entities

encapsulating control

along with criteria to govern it (tasks / goals)

Artefacts are

passive / reactive entities

encapsulating services / functions

shaping agent environment according to MAS needs

The A&A approach to the engineering of complex MAS exploits

agents to model pro-active goal/task-oriented entities

artefacts to model objects or tools dynamically constructed, used,modified by agents in their activities



Boundary Artefacts I

Admissible events

The first issue is to map activities of any sort upon a set of admissibleevents, that is, those events that are accepted and handled by the MAS.

Apart from an appropriate model, this requires suitably-definedarchitectural abstractions embedding such a mapping.



Boundary Artefacts II

Boundary artefacts

This is the role of boundary artefacts, which mediate

between agents and the MAS

between the MAS and its environment

In particular, we envision a MAS architecture in which each agent andeach environmental resource is associated to its own boundary artefact,working as:

a proxy for the agent / resource within the MAS

a sort of interface for the agent / resource towards the MAS



Coordination Artefacts

Once brought within a MAS by a boundary artefact, an admissible eventhas to be properly handled to possibly generate other events and / orcomputational activities, defining the overall behaviour of a MAS.

Coordination artefacts

This is the role of coordination artefacts [Omicini et al., 2004], which

perceive admissible MAS events

associate them to computational activities implementing coordinationlaws

possibly generating further events—thus giving raise to so-calledevent chains



An Event-driven Architecture I

Figure : An event-driven architecture built around the notions of boundary andcoordination artefacts



An Event-driven Architecture II

I

I

I

I

I

S

S

R

R

Figure : A&A artefacts: individual, social, and resource artefacts



An Event-driven Architecture III

With respect to the classification of artefacts introduced by the A&Ameta-model [Omicini et al., 2006a]:

individual and resource artefacts are basically represented by boundaryartefacts

social artefacts play roughly the role of coordination artefacts

! more precisely, an articulated association of boundary and (individual)coordination artefacts is required for A&A individual artefacts


A Concrete Event-driven Architecture in TuCSoN

Outline

1 Motivation




5 Perspectives



Architectural Mapping upon TuCSoN I

The abstract architecture sketched above essentially models complex MASas composed of:

proactive entities, as agents, environment resources and thespace-time fabric

reactive entities, like boundary and coordination artefacts

connected together by a net of co-ordinated events.



Architectural Mapping upon TuCSoN II

TuCSoN coordination media

First of all, it is quite easy to map coordination artefacts upon ReSpecTtuple centres [Omicini and Denti, 2001], which are the coordinationabstraction provided by TuCSoN.

ReSpecT tuple centres

computational activities devoted to MAS coordination can berepresented in terms of the ReSpecT logic-based specificationlanguage [Omicini, 2007]

ReSpecT allows admissible events to be associated to reactions

ReSpecT reactions atomic, transactional computational activitiescarried out by tuple centre themselves



Architectural Mapping upon TuCSoN III

Agent Coordination Contexts

Then, two middleware abstractions play the role of boundary artefacts inTuCSoN:

Agent Coordination Contexts (ACC) [Omicini, 2002], for agents

Transducers [Casadei and Omicini, 2009], for resources



Architectural Mapping upon TuCSoN IV

Figure : TuCSoN event-driven architecture: ACC and transducers are theboundary (respectively, individual and resource artefacts), whereas ReSpecT tuplecentres are the coordination (social) artefacts



Architectural Mapping upon TuCSoN V

On the role of ACC

ACC play the role of security and organisation abstractions[Omicini et al., 2006b]

Each agent has an associated ACC that mediates all the agentinteractions with the TuCSoN system, working

both as its representative within the TuCSoN-coordinated MASand as its interface towards the MAS itself, providing the agent withavailable operations



Architectural Mapping upon TuCSoN VI

On the role of transducers

Transducers [Casadei and Omicini, 2009] are in charge of representingindividual resources, along with their own peculiar ways of interacting

Each portion of the MAS environment represented by a resource isassociated to its specific transducer, capable of two-way interaction tomap meaningful resource events upon admissible MAS events



Swarm Steering Scenario I

Suppose you want to coordinate the motion of a swarm of robots soas to reach a “uniform” distribution in space, in which each robot isequi-distant from its neighbours

By adopting our reference event-driven architecture, you’ll have:

a number of agents, responsible for motion planning and policiesadjustmentsa number of sensors to perceive motion eventsa number of actuators to perform motion actionsa number of coordination media to enable the distributed algorithm incharge of enforcing uniform spatial distribution of the robots



Swarm Steering Scenario II

Furthermore, by adopting TuCSoN architecture, you’ll assign:

one ACC for each agent, to properly model agents (unpredictable)behaviour as seen by the system

one Transducer for each sensor and actuator, to properly model theportion of environment the system has to interact with

one ReSpecT tuple centre for each coordination mediarequired—adding tuple centres can help, e.g., to scale-up with the sizeof the application



Swarm Steering Scenario III

Figure : TuCSoN event-driven architecture on a case study: Managers allowfailures to be properly handled, and of transducers / ACCs to be dynamicallyadded/removed



Swarm Steering Scenario IV

Doing so enables us to:

define which events are of your interestmodel their structureassociate them to computational activities to be carried out withinReSpecT tuple centres—thus, transparently from the agents’standpointdeliver events of any sort to the interested receivers—e.g. agents

In our scenario, for instance, interesting events to be properlymodelled and handled are:

an agent leaving a place to reach another, closer to the desired spatialuniform distributionan agent approaching a place from another, as a result of a motionphase toward a better configurationan agent multicasting its new position to neighbours, so as to triggertheir own position adjustment


Perspectives

Outline

1 Motivation




5 Perspectives


Perspectives

Benefits

Facing situatedness at the (MAS) system level, rather than at the(agent) individual component level

Bridging between the (low-level) environment level representation,and the (high-level) cognitive level of intelligent agents

Providing engineers with a principled architecture for dealing withcomplex environments

Delivering languages, tools, and methodologies that coherentlysupport the architecture


Perspectives

Perspectives

Engineering complex MAS is mostly dealing with a complex networkof events

Both formal tools – like, say, Petri Nets – and new tools from thefield of Complex Networks may tell us something new about MASengineering

Interaction as a key point for interdisciplinary study of complexsystems of any sort [Omicini and Contucci, 2013]


Perspectives

Further References

Paper

Reference [Omicini and Mariani, 2013]

APICe http://apice.unibo.it/xwiki/bin/view/

Publications/EventsituatedmasPnse2013

Presentation

APICe http://apice.unibo.it/xwiki/bin/view/Talks/

EventsituatedmasPnse2013

Slideshare http://www.slideshare.net/andreaomicini/om-pnse2013


http://apice.unibo.it/xwiki/bin/view/Publications/EventsituatedmasPnse2013

http://apice.unibo.it/xwiki/bin/view/Publications/EventsituatedmasPnse2013

http://apice.unibo.it/xwiki/bin/view/Talks/EventsituatedmasPnse2013

http://apice.unibo.it/xwiki/bin/view/Talks/EventsituatedmasPnse2013

http://www.slideshare.net/andreaomicini/om-pnse2013

Acknowledgements

Thanks to . . .

The authors would like to thank the organisers of PNSE’13 andModBE’13 – and in particular Daniel Moldt – for inviting ourcontribution

This work has been supported by the EU-FP7-FET Proactive projectSAPERE – Self-Aware PERvasive service Ecosystems, under contractno. 256873


References

References I

Bellifemine, F. L., Caire, G., and Greenwood, D. (2007).

Developing Multi-Agent Systems with JADE.

Wiley.

Casadei, M. and Omicini, A. (2009).

Situated tuple centres in ReSpecT.

In Shin, S. Y., Ossowski, S., Menezes, R., and Viroli, M., editors, 24th AnnualACM Symposium on Applied Computing (SAC 2009), volume III, pages1361–1368, Honolulu, Hawai’i, USA. ACM.

Cossentino, M., Gaglio, S., Sabatucci, L., and Seidita, V. (2005).

The PASSI and agile PASSI MAS meta-models compared with a unifying proposal.

In Pechoucek, M., Petta, P., and Varga, L. Z., editors, Multi-Agent Systems andApplications IV, volume 3690 of LNCS, pages 183–192. Springer.

4th International Central and Eastern European Conference on Multi-AgentSystems, CEEMAS 2005, Budapest, Hungary, September 15-17, 2005, Proceedings.


References

References II

Goldin, D. Q., Smolka, S. A., and Wegner, P., editors (2006).

Interactive Computation: The New Paradigm.

Springer.

Hallenborg, K., Jensen, A. J., and Demazeau, Y. (2007).

Reactive agent mechanisms for manufacturing process control.

In 2007 IEEE/WIC/ACM International Conferences on Web Intelligence andIntelligent Agent Technology Workshops (WI-IATW ’07), pages 399–403,Washington, DC, USA. IEEE Computer Society.

Molesini, A., Omicini, A., Denti, E., and Ricci, A. (2006).

SODA: A roadmap to artefacts.

In Dikenelli, O., Gleizes, M.-P., and Ricci, A., editors, Engineering Societies in theAgents World VI, volume 3963 of LNAI, pages 49–62. Springer.

6th International Workshop (ESAW 2005), Kusadası, Aydın, Turkey,26–28 October 2005. Revised, Selected & Invited Papers.


References

References III

Omicini, A. (2002).

Towards a notion of agent coordination context.

In Marinescu, D. C. and Lee, C., editors, Process Coordination and UbiquitousComputing, chapter 12, pages 187–200. CRC Press, Boca Raton, FL, USA.

Omicini, A. (2007).

Formal ReSpecT in the A&A perspective.

Electronic Notes in Theoretical Computer Science, 175(2):97–117.

5th International Workshop on Foundations of Coordination Languages andSoftware Architectures (FOCLASA’06), CONCUR’06, Bonn, Germany,31 August 2006. Post-proceedings.


References

References IV

Omicini, A. and Contucci, P. (2013).

Complexity & interaction: Blurring borders between physical, computational, andsocial systems. Preliminary notes.

In Badica, C., Nguyen, N. T., and Brezovan, M., editors, 5th InternationalConference on Computational Collective Intelligence Technologies and Applications(ICCCI 2013), Craiova, Romania.

Invited Paper.

Omicini, A. and Denti, E. (2001).

From tuple spaces to tuple centres.

Science of Computer Programming, 41(3):277–294.

Omicini, A. and Mariani, S. (2013).

Coordination for situated MAS: Towards an event-driven architecture.

In Moldt, D. and Rolke, H., editors, Proceedings of the International Workshop onPetri Nets and Software Engineering (PNSE’13), volume 989 of CEUR WorkshopProceedings. Sun SITE Central Europe, RWTH Aachen University.


References

References V

Omicini, A., Ricci, A., and Viroli, M. (2006a).

Agens Faber: Toward a theory of artefacts for MAS.

Electronic Notes in Theoretical Computer Science, 150(3):21–36.

1st International Workshop “Coordination and Organization” (CoOrg 2005),COORDINATION 2005, Namur, Belgium, 22 April 2005. Proceedings.

Omicini, A., Ricci, A., and Viroli, M. (2006b).

Agent Coordination Contexts for the formal specification and enactment ofcoordination and security policies.

Science of Computer Programming, 63(1):88–107.

Special Issue on Security Issues in Coordination Models, Languages, and Systems.

Omicini, A., Ricci, A., and Viroli, M. (2008).

Artifacts in the A&A meta-model for multi-agent systems.

Autonomous Agents and Multi-Agent Systems, 17(3):432–456.

Special Issue on Foundations, Advanced Topics and Industrial Perspectives ofMulti-Agent Systems.


References

References VI

Omicini, A., Ricci, A., Viroli, M., Castelfranchi, C., and Tummolini, L. (2004).

Coordination artifacts: Environment-based coordination for intelligent agents.

In Jennings, N. R., Sierra, C., Sonenberg, L., and Tambe, M., editors, 3rdinternational Joint Conference on Autonomous Agents and Multiagent Systems(AAMAS 2004), volume 1, pages 286–293, New York, USA. ACM.

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References

References VII

TuCSoN (2013).

Home page.

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Environment as a first-class abstraction in multi-agent systems.


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http://tucson.apice.unibo.it

Coordination for Situated MAS:Towards an Event-driven Architecture

Andrea [email protected]

Stefano [email protected]

DISIAlma Mater Studiorum–Universita di Bologna

ModBE’13 / PNSE’13Universita di Milano – Bicocca

25 June 2013




http://www.disi.unibo.it

http://www.unibo.it

http://apice.unibo.it/xwiki/bin/view/Events/Modbe2013

http://apice.unibo.it/xwiki/bin/view/Events/Pnse2013

http://www.unimib.it/