Baldoni, M.

Baroglio, C.

Micalizio, R.

Tedeschi, S.

English

Institutional Research Information System University of Turin

Robust JaCaMo Applications via Exceptions and AccountabilityDemonstration TrackMatteo BaldoniUniversità degli Studi di Torino, Dip. di InformaticaTorino, Italymatteo.baldoni@unito.itCristina BaroglioUniversità degli Studi di Torino, Dip. di InformaticaTorino, Italycristina.baroglio@unito.itRoberto MicalizioUniversità degli Studi di Torino, Dip. di InformaticaTorino, Italyroberto.micalizio@unito.itStefano TedeschiUniversità degli Studi di Torino, Dip. di InformaticaTorino, Italystefano.tedeschi@unito.itABSTRACTRobustness is the degree to which a system can function correctlyin the presence of perturbations. We present two extensions to theJaCaMo agent platform to realize robust MAS applications. Thefirst extension delivers an exception handling mechanism suited forMAS; the second one is grounded on the notion of accountability tocreate feedback chains among the agents. Both extensions providehigh-level abstractions that facilitate the design and developmentof a MAS that meets robustness requirements.KEYWORDSJaCaMo; Engineering MAS; Exception Handling; AccountabilityACM Reference Format:Matteo Baldoni, Cristina Baroglio, Roberto Micalizio, and Stefano Tedeschi.2023. Robust JaCaMoApplications via Exceptions andAccountability: Demon-stration Track. In Proc. of the 22nd International Conference on AutonomousAgents and Multiagent Systems (AAMAS 2023), London, United Kingdom,May 29 – June 2, 2023, IFAAMAS, 3 pages.1 INTRODUCTIONRobustness, “the degree to which a system or component can functioncorrectly in the presence of invalid inputs or stressful environmentalconditions” – generally called perturbations [13], is a crucial require-ment of distributed software systems [9, 10, 14, 15]. Multi-AgentSystems (MAS) [18] are an effective approach to realize distributedsystems bymeans of heterogeneous, and autonomous agents. Agentorganizations (MAO), in particular, provide abstractions for modu-larizing code spread over many components, and orchestrate theirexecution by way of norms. JaCaMo [8] is one of the best-knownplatforms for implementing MAOs, but it focuses on providing themeans for capturing the normal, correct behavior of the system andlacks of structural mechanisms allowing agents to exchange andpropagate information (feedback) when they face perturbations.As in [1], the availability of feedback about perturbations is crucialto build robust distributed systems. Also MAS robustness shouldground on the ability to convey feedback about perturbation to theagents that can handle it. But since agents generally are peers, andare not related by relationships like caller-callee or parent-child,Proc. of the 22nd International Conference on Autonomous Agents and Multiagent Sys-tems (AAMAS 2023), A. Ricci, W. Yeoh, N. Agmon, B. An (eds.), May 29 – June 2, 2023,London, United Kingdom. © 2023 International Foundation for Autonomous Agentsand Multiagent Systems (www.ifaamas.org). All rights reserved.the realization of robustness should occur through the definitionof distributions of responsibilities among the agents, that becomepart of the MAO. This demonstration presents two extensions tothe JaCaMo platform which allow building robust agent organiza-tions. The first borrows from software engineering the conceptsof exception and exception handling, while the second relies on thenotion of accountability. Exception handling is suitable for treatingperturbations anticipated at design time (i.e., exceptions) by activat-ing handlers, that are also specified at design time. Accountability,instead, defines feedback “channels” that agents can use at runtimeto gain situational awareness about what occured and then takeactions. Raising and handling exceptions as well as asking and re-turning for an account will be tasks, under the responsibility ofspecific agents. The two extensions provide the means for repre-senting such tasks as goals, and for distributing the reponsibilitiesof such goals to the capable agents. Note that each such goal can beassigned to many agents, specifying the minimum and maximumcardinality of how many agents need to achieve the goal (as stan-dard in a JaCaMo organization specifications). Moreover, we allowspecifying many raising and handling goals for each exception,and many requesting, accounting and treatment goals (possiblyinvolving many agents) for each accountability.2 JACAMO + EXCEPTIONSWe consider a production cell for metal plates inspired to [16]. Thesystem involves five robots (agents) that coordinate their activitiesfor producing plates. The process can be realized as a JaCaMoorganization where the organizational goal of producing a plate isdecomposed into sub-goals the robots should achieve. We introducethe management of the possible malfunction of one of the motors ofthe elevating rotary table (ERT ). Such a condition should be detectedas soon as possible to stop the production and schedule repair. Afirst solution would be to add the treatment of the perturbation as apart of the original goal decomposition. This solution, however, isstrongly discouraged by practice. In fact, mixing business logic andexception handling logic complicates the verification of processes aswell as later modifications [11]. Our proposal is to keep the originalgoal decomposition distinct from any malfunction treatments, andintroduce new abstractions for modeling treatments as exceptionsto be raised and handled1. For instance, the following NotificationPolicy complements the goal decomposition.1Source code available at http://di.unito.it/moiseexceptions.Demonstrations AAMAS 2023, May 29–June 2, 2023, London, United Kingdom30501 <notification−policy id="npTable" target="turnTableMoveUp"2 condition="scheme_id(S) & failed (S,turnTableMoveUp)">3 <exception−specification id="exMotor">4 <exception−argument id="motorNumber" arity="1" />5 <raising−goal id="notifyStoppedMotorNumber" />6 <handling−goal id="scheduleTableMotorFix" />7 </exception−specification>8 </notification−policy>The policy specifies how the ERT motor malfunction exceptionis handled by scheduling repair. In fact, the policy targets goalturnTableMoveUp, assigned to ERT in the original decomposition,and is activated whenever such a goal fails (see the condition ex-pressed in NOPL syntax [12]). The policy then specifies the type ofexception, exMotor, and its argument: the number identifying themotor affected by the problem (fundamental in order to act on theright motor). The exception, thus, amounts to a piece of informationto be exchanged between some agent that detects the problem, andsome that can handle it. To model this relationship, we extend thenotion of goal, native in JaCaMo, in two ways. A Raising Goal isused to make an agent produce an exception (i.e., the structuredpiece of information), and raise it by making this exception avail-able, through the organization, to the agents that can handle it. AHandling Goal is used to model the treatment of an exceptionwhen it becomes available. Both types of goals can be included inagent missions, as any other goal in JaCaMo. This has an importantconsequence: whenever an agent enacts an organizational role, it isasked to commit to all the goals included in the missions associatedwith that role, including raising and handling goals. So, from theperspective of agent programming, the treatment of exceptions iscompletely transparent: agents just need to bring about their goalswhen asked to, independently of whether these goals are in theoriginal decomposition or part of some notification policy.In the example, the goals notifyStoppedMotorNumber and sched-uleTableMotorFixmust be included in the missions of agents havingthe right capabilities for completing them. So, either ERT itself couldthe exception raiser, or the exception could be raised by external,observing agent. An important feature of our proposal, in fact, is aclear separation of concerns among the agents where a perturbationoccurs, where it is detected, and, then, where it is treated. That is,the agent whose goal fails may be different from the agent thatactually detects the failure and raises the exception. And the agenthandling the exception is usually different from the one that raisedit. The details of the implementation can be found in [2, 3, 6, 17].3 JACAMO + ACCOUNTABILITYAccountability allows agents to get runtime information to be usedin their decision making. Specifically, a party, named account-taker(a-taker) is entitled to ask for an account about a goal of interestto another party, named account-giver (a-giver), that is obligedto provide such an account upon request. Through accountability,thus, agents have access to information otherwise inaccessible, and,hence, have greater awareness of what is going on in the overallsystem. This allows the agents to take advantage of opportunities,and to adapt to changing system conditions.For instance, suppose the production cell is part of a productionplant that should possibly never be stopped. Assume that an agentis in charge of supervising the production process. This agent can,under certain conditions, ask the feed belt robot the amount of platesstill to be processed. Depending on such a number, the supervisorcan decide to slowdown the production, in order to avoid a full stop.Also in this case, this behavior could be included within the originalgoal decomposition of the production process, but the result wouldbe a mix-up between business and control logic. Our solution keepsseparate business and control logic, and exploits accountability toallow the supervisor to obtain the needed information from thefeed belt robot. The following Accountability Agreement, includedin the definition of the organization, serves this purpose2.1 <accountability−agreement id="aa1">2 <target id="conveyPlateToTable" />3 <requesting−condition value="true" />4 <account−template>5 <account−argument id="availablePlates" arity="1" />6 <goal id="requestRemainingStock" atype="requesting" />7 <goal id="notifyRemainingStock" atype="accounting" />8 <goal id="slowDownProduction" atype="treatment"9 when="account(_, availablePlates (N)) & N <= 10 & N > 0" />10 <goal id="stopProduction" atype="treatment"11 when="account(_, availablePlates (0)) " />12 </account−template>13 </accountability−agreement>The accountability agreement is the abstraction we offer to allowaccounts to flow from a-givers to a-takers. Specifically, an account-ability agreement targets a goal, e.g., conveyPlateToTable, whichrepresents the object of the account. An agreement is activated bya requesting condition, that can even be true, meaning that it canbe asked at any time throughout the execution. An important partof the agreement concerns the structure of the account, and how itcan be asked and provided. The structure of the account is given asa list of arguments with their corresponding arity. In our example,a single argument availablePlates with arity one, is sufficient toconvey the number of plates in the queue. Concretely, we leveragedthe model presented in [4] and the formalization from [5, 7].Tomodel the request and the notification of an accountwe extendJaCaMo goals, as we did for exceptions, by introducing the notionsof Requesting Goal and Accounting Goal. Intuitively, when anagent wants to get some specific information outside its context,and has the permission to ask for them, the agent needs just to ac-complish a requesting goal. This activates, by way of the normativesystem of the organization, the associated accounting goal specifiedin the agreement. For instance, when goal requestRemainingStockis marked as achieved, goal notifyRemainingStock is activated, andthe agent responsible for it (i.e., feed belt) receives the obligation tocarry it out. The agreement reports also an optional TreatmentGoal. When specified, the goal specifies how the account should beaddressed by the a-taker. In our scenario, there are two alternativetreatment goals: one to be activated when the number of availableplates is between 0 and 10, then the production is slowed down;and one to be activated when such a number is 0, and hence all theproduction cell is stopped.Also in this case, the requesting, the accounting and the treat-ment goals are part of role missions, as for standard JaCaMo goals.By committing to suchmissions, agents take on the responsibility toperform these goals whenever a corresponding obligation is issuedby the normative system of the organization.2Source code available at http://di.unito.it/moiseaccountability.Demonstrations AAMAS 2023, May 29–June 2, 2023, London, United Kingdom3051ACKNOLEDGEMENTSThis publication is part of the project NODES which has receivedfunding from the MUR –M4C2 1.5 of PNRR with grant agreementno. ECS00000036.REFERENCES[1] David L. Alderson and John C. Doyle. 2010. Contrasting Views of Complexityand Their Implications for Network-Centric Infrastructures. IEEE Tr. on Sys.,Man, and Cyber. 40, 4 (2010).[2] Matteo Baldoni, Cristina Baroglio, Olivier Boissier, Roberto Micalizio, and StefanoTedeschi. 2021. Demonstrating Exception Handling in JaCaMo. In Advancesin Practical Applications of Agents, Multi-Agent Systems, and Social Good. ThePAAMS Collection - 19th International Conference, PAAMS 2021, Salamanca, Spain,October 6-8, 2021, Proceedings (Lecture Notes in Computer Science, Vol. 12946),Frank Dignum, Juan M. Corchado, and Fernando De La Prieta (Eds.). Springer,341–345. https://doi.org/10.1007/978-3-030-85739-4_28[3] Matteo Baldoni, Cristina Baroglio, Olivier Boissier, Roberto Micalizio, and Ste-fano Tedeschi. 2021. Distributing Responsibilities for Exception Handling inJaCaMo. 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Robust JaCaMo Applications via Exceptions and Accountability

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Robust JaCaMo Applications via Exceptions and Accountability

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