Inthissectionweprovideanoverviewonsystemsthatimplementtheapproachespresentedearlier.Wefocushereona comparisonofthesystemsw.r.t.theirfeatures(e.g.supportedsemanticsandreasoningproblems)andunderlyingconcepts.
Ourgoalistoprovidea comprehensivestudyofthestrengthsofeachtool,wherethereadercanlookup theappropriate toolfortheproblemathand.Thefeaturesofthepresentedsystemsarenaturallysubjecttochangeinthefuture.Wenote thatthelandscapeofcurrentlyavailablesoftwareisveryheterogeneous:Sometoolsaretailoredtographicalrepresentations oftheusedalgorithms andresultswhereas othersareparticularlytuned towardsperformance.Withintheargumentation communitythereiscurrentlynoconsensusonwhichinstancesarerepresentativeforcomparingdifferentimplementations w.r.t. performance. Moreover, independent benchmark suites are not available. Hence, a systematic, fair andlonger-term stablecomparisonw.r.t. run-timeperformance iscurrentlynot possible,andwe refer tocurrentlyongoing developments withinthecommunitythatseekforastandardizedsystemcompetitionofargumentationsystems[48,123,43].Nevertheless, whereavailable,wegivereferencestoarticlesthatdealwithaperformancecomparisonofparticulartools.
Table 2summarizessystemsforabstractargumentation.TheURLlinkstothewebpageoftherespectivesystem,where sourcecodeanddocumentationorthewebfront-end(ifavailable)canbefound.Additionally,thetablecontainsareference tothesectionwherethealgorithms underlyingthetoolarediscussed.Thelastcolumncontainsthereferencetothemain articleofthe tool.In caseno particulararticleon thetool was published,we referenceherethepaperthat presentsthe theoreticalbackgroundofthetool.
Table 3liststhetechnicalcharacteristicsoftheconsideredsystems.The“GUI”columnnotonlyindicatestheavailability ofa full-fledged graphical userinterface butalso contains informationabout availability offront-ends fordemonstration
Table 3
Argumentationsystems:technicaldetails.
System name Platform Language GUI Command line Library
ArgSemSAT independent C++ – yes no
ArgTools independent C++ – yes no
ASPARTIX as ASP solver ASP web yes no
CEGARTIX Unix C++ – yes no
CompArg Windows Delphi stand-alone no no
ConArg independent Java, C++ stand-alone yes yes
Dung-O-Matic independent Java web (via OVAGen) no yes
Dungine (ArgKit) independent Java web (via OVAGen), demo GUI no yes
dynPARTIX Unix C++ – yes no
PyAAL (+ArguLab) independent Python web (ArguLab) yes no
Table 4
SystemcapabilitiesshowingwhichsystemcanreasonC(redulously),S(keptically)orisable toE(numerate),respectivelyV(erify)asolution.Implicitreasoningsupportisdenotedby theitaliclettersCandS.
purposes.Column“commandline”denotesthatthesoftwareisaccessibleviacommandlineinterface,and“library”specifies thattheimplementationcanbeaccessedviaaspecifiedsoftwareinterface.
In Table 4weprovidean overviewonthesupportedsemantics andreasoningproblemsofthesystems.Notethat this table onlycontainsthesemantics andreasoningproblemsweconsiderthroughoutthiswork(seeSection 2).Additionally, wealsoincludeimplicitreasoningsupportinthetable,denotedbytheitaliclettersCandS.Thatis,weknowthatcredulous reasoningyields thesameanswerforanyAFandargumentw.r.t.preferred,complete andadmissiblesemantics.Similarly, skepticalreasoningforcompleteandgroundedsemanticsreturnthesameresult.Since thegroundedextensionisunique, credulousandskepticalreasoningareequivalentforgroundedsemantics.
The strengths of each tool are summarized in Section 5.1. There, we go into detail of system-specific characteristics, such asparticularGUI-basedfeatures,support foradditionalreasoningproblemsorperformance-relevantdetails.Ifa sys-tem iscapableof computingfurthersemantics,such asideal[124],eager[125],cf2[126], stage2[127],resolution-based grounded[128]wenotethisinthecorrespondingsystemparagraph.
5.1. Systemproperties
ArgSemSAT The high-performance systemArgSemSAT is builton top ofmodern SAT solvers in such that it incorporates an iterativeSAT-procedure. Inparticular, itimplementsthePrefSat approach[82] fromSection3.1.3.The procedurerelies on iteratively generating complete extensions/labelings andextending them iteratively to preferred extensions. Asimilar approach is takenby CEGARTIX,whereskeptical acceptanceof preferredsemantics (among other query-based reasoning problems) iscomputed. The implementationof PrefSatshowed good performance compared to ASPARTIX(even withits metaspapproach)andArgTools[82].ArgSemSATallowstochoosebetweendifferentSAT-solversandprocessesinputinthe ASPARTIX inputformat. Infutureitisalsosupposed toincludedirectalgorithms basedonthe SCC-recursiveschema[22, 129].
ArgTools Thissystem aimsto provide afast implementationof alabeling-based algorithmfor enumeratingall preferred extensions(cf.Algorithm 4).Whilethemainfocusoftheresearchbehindthistoolisdirectedtowardsefficientenumeration of preferredsemantics [36] there are severalother results. First,enumeration algorithms forseveralother semantics,i.e.
those depictedinTable 4andideal,wheredevelopedin[105].Second,in[36] theauthors presentan implementationof optimizations forcredulous andskeptical reasoningwith preferredsemantics. Thislineof research compares the perfor-mance ofdifferentlabelingbased algorithms andinparticular givesempirical evidence,by comparingthe algorithms on
randomly generatedinstances, that thenewly proposed algorithms arethe fastestones. Some of thealgorithms are also comparedwithASPARTIX(usingtheDLVsolver)anddynPARTIXwhereArgToolsagainshowedgoodperformance.
ASPARTIX The “AnswerSetProgrammingArgumentationReasoningTool”[30] isbasedonreductionstoASPasdiscussed inSection3.3.ItconsistsofacollectionofASPencodings,whereeachencoding,augmented byagivenAFinformofASP facts, canbe givenasinput toan ASPsolverinorder tocompute theextensions.Formostsemantics, ASPARTIXprovides encodingsforthesolverDLVaswell asgringo/clasp(D).Followingthe reductionapproach,ASPARTIX’sperformance scales withnewversionsofthesesolvers.Furthermore,thesystemisplatformindependentinthesensethatitrunsonany sys-tem supporting the ASP solvers. ASPARTIX also offers a web front-end, where anyargumentation framework aswell as its extensions can be inspected graphically. Aparticularly usefulfeature of thissystem isthat itsupports many seman-tics andsolves variousreasoning problems.In additionto thesemantics in Table 4, ASPARTIXsupports ideal,cf2, stage2 andresolution-basedgroundedsemantics.SinceASPsolverssupportenumerationandcredulousaswellasskeptical query-basedreasoning,thiscandirectlybeutilizedby ASPARTIX.Thesystemisoftenusedasareferencesysteminperformance comparisons[21,82,31,36,37,83,98,105,130,45,44,131].
CEGARTIX The “Counter-ExampleGuidedArgumentationReasoning Tool”[21] is builtontop ofmodern SATsolvers, and relies on an iterative procedure ofSAT-calls (see Algorithm 1). As a command-linetool, CEGARTIX is built towards per-formanceandcomputestheskepticalacceptanceofan argumentw.r.t.preferred,semi-stableandstagesemantics andfor thelasttwo alsocredulousacceptance.LikeArgSemSAT[82],whichreliesoniterativeSATcallsforenumeratingpreferred labelings, CEGARTIX can be seen as a sortof hybrid approach between direct and reduction-based methods, since only certain sub-tasks are delegated toa SAT solver. CEGARTIX isavailable onlineasa binary. The systemallows the userto configurewhichSAT-solvershewantstouse.Beingbasedonareductionapproach,CEGARTIXscaleswithnewerversionsof SATsolversandthesystemhasbeenshowntobecompetitivew.r.t.ASPARTIX[21] andalsoprocessestheASPARTIXinput format.
CompArg CompArg [38] is intended for determining credulous acceptance of arguments w.r.t. preferred semantics and enumeratinggrounded,preferred,stableandsemi-stableextensions.Itimplementsthelabeling-basedapproachaspresented inSection 4.1(Algorithm 4).Writtenin Delphi,theexecutable forWindowsis publiclyavailable. Thesystemcomes with manyexamples,whichsuitsitsmaineducationalaimofillustrationofthesemantics.Duetothispurposeitisnotprimarily builtforhighperformance.The tool consistsofaGUIthat illustrates thecomputation oftheacceptancestatus,eitherby providingproofs orrefutationsofarguments. Additionally,several exampleinstancesare provided.Therefore, CompArgis particularlyusefulwhen itcomes toget a deeperunderstanding oftheunderlying algorithm.Besides decidingcredulous acceptance,theresultingextensionscanbeenumerated.
ConArg The systemConArg [26] followsareduction-basedapproach towardsCSPsaspresentedinSection 3.2.Internally, thetoolusessophisticatedJavaimplementationsofCSPengines(JaCoP).Itsperformancethusscaleswithnewerversionsof theseengines,anditisplatform-independentthroughtheuseofJava.Itsupportstheenumerationofextensionsformany semantics(seeTable 4)andiscapableofverifyingwhetheragivensetisapreferredextension.Thetoolfeaturesasimple and intuitive graphical user interface for inspecting the AF andthe extensions at hand.It supports the ASPARTIX input format forAFs, andalso allows togenerate random (weighted)argumentation frameworks.ConArg is alsoavailable asa web-interfacewithaninteractivegraphicalrepresentation.Recently,thesecondversionofConArgwithsomemodifications wasreleased[131,43,44].Toimprovetheperformance,ConArg2isnowbasedonGecode, anefficientC++ environmentfor constraint-basedapplications.ConArg2isavailable asapre-compiled commandlinetool forLinux. Besidesthefeaturesof ConArg, ConArg2alsoallows forcredulousandskepticalreasoningforadmissible,stableandcompletesemantics. ConArg andConArg2showedgoodperformancecomparedtoASPARTIXandDung-O-Matic[130,131].
Dung-O-Matic Dung-O-Matic isbasedon dialecticalproof-procedures(see Section 4.2) andincludesimplementations for many differentsemantics. Besides support for most ofthe semantics listed inTable 4, idealand eager extensions fora given AF can be computed. Implemented as a Java library, it can be flexibly used across platforms. For demonstration purposes, it isaccessible via the tool OVAgen.15 OVAgenis a web-based softwarewhere argumentationframeworks can bedrawngraphicallyandtheresultingextensionsarevisualized.ApreliminaryperformancecomparisonagainstASPARTIX andConArg is published by Bistarelli etal.[130].Although thiswork showsthat thetool is outperformed by the other two systemswhencomputingcompleteorstableextensions,one hastonote that furthercomparisonsand, inparticular, real-worldinstancesarenecessarytogainabetterpictureofthetool’sperformance.
Dungine(partofArgKit) Dungine [109] implements algorithms based on dialogue games, and currently provides native supportforgroundedandpreferredsemantics.ItispartofArgKit,aJavalibraryintendedforbuildingcustomsoftwarebased on argumentation. For demonstration purposes, the ArgKit package includes examples of GUI applications. Additionally,
15 http://ova.computing.dundee.ac.uk/ova-gen/.
similar to Dung-O-Matic,thesoftware isintegratedin thetool OVAgen.Since thesource codeismade publiclyavailable undertheLGPLlicense,itcanbeintegratedinotherprojects.
dynPARTIX The concept underlyingthe “Dynamic ProgrammingArgumentationReasoning Tool” [42,115] isbased on dy-namicprogramming, wheretheinstanceisdecomposedbeforesolving(seeSection 4.3).Thetoolexploitsthestructureof thegivenargumentationframework,wherethedecompositionisconstructedbasedonheuristics.Hence, itsrun-time per-formanceisparticularlygoodforinstanceswithtree-likestructures.Thetool,implementedinC++,iscurrentlyavailableas Linuxexecutable.Aspecialcharacteristicthatdifferentiatesitfromtheothersystemspresentedhereisitsabilitytoprovide theoverallnumberofsolutionswithoutexplicitenumeration.
PyAAL(+ArguLab) The“PythonAbstractArgumentationLibrary”implementslabeling-basedproceduresfordeterminingthe justificationstatusofargumentsandforenumeratingthelabelingsformanysemantics(seeSection4.1).Inadditiontothe functionality summarizedin Table 4,PyAAL is ableto compute the ideal andeager labeling,aswell asdetermining the corresponding justificationstatus.ArguLab [107] isaweb front-endthat allowstodemonstratethe capabilitiesofPyAAL.
Within ArguLab, in a first step the argumentation framework is constructed. Next,based on the selected semantics the labelings associated withthe argumentsare visualized. The tool allows tointeractively analyze thejustificationstatus of arguments.NotethatArguLabisdesignedfordemonstrationpurposesonly,buttheunderlyingcodeofPyAALcanbeused withoutrestrictions(GPLlicensed).Itsparticularstrengthliesinthefactthatitsupportsabroadnumberofsemanticsand solvesseveralreasoningproblems.
5.2. Summary
The systemcomparisonillustratesthediverselandscapeofavailable toolsforabstractargumentation:Whilesome sys-tems covera widerangeofdifferentsemantics(e.g.,ASPARTIX,ConArg,Dung-O-Matic,andPyAAL), othersare well-suited for illustrationanddemonstration purposes of thealgorithms (e.g., CompArg andDungine) orare tailored towards solv-ingparticularproblemsefficiently(e.g.,ArgSemSAT,ArgTools,CEGARTIXanddynPARTIX).Also,diversityisobservablewhen consideringthesupportedsemanticsandsolvablereasoningproblems(seeTable 4).Amongtheconsideredsystems,no se-manticsandreasoningproblemissupportedbyalltools.Additionally,topromotetheir functionality,severaltoolsprovide accessto their systemsvia a webinterface (e.g.,ASPARTIX,ConArg, Dung-O-Matic,DungineandPyAAL), whichallows to testthesystemwithoutthenecessitytodownloadorinstallsoftware.
Theavailablerun-timecomparisonsdonotindicatethatonesystemoutperformsallothers.However,weobservedthat ASPARTIX is, in most cases, used as a base line system for performance comparisons. To give a clearer picture on the performance aspects ofthetools,thereis aneedforindependently createdandpublicly availablebenchmark suites.This (andalsoideasonrunningevenapublicsystemcompetitionforargumentationsystems)isdiscussedwithinthecommunity (see,e.g.,[132]).
Additionally, besides run-time performance, many other aspects are important fora good system, including intuitive design,versatility,extendability,andalsosourcecodeavailabilityorongoingsupportanddevelopment ofthesystem.Each toolhasitsuniquecharacteristicsandadvantages,thereforethechoicefortherighttoolmainlydependsontheproblemat hand.
6. Discussion
We concludeour survey on implementation of abstract argumentation withvarious issues we have not touched yet.
Thisincludesmethodsforfurthersemantics(Section6.1)andcomplementaryaspectsforevaluatingabstractargumentation frameworks,forinstance,pre-processing(Section6.2).InSection6.3,wegivepointerstosystemswhichareinacertainway concernedwithabstractargumentation,buthaveamoregeneralaim(infact,methodsaspresentedinthissurveycouldbe usedwithinsuchsystems).Wethenproceedwithaglobalsummaryanddiscussdirectionswhichwebelieveareimportant forfuturedevelopments.
6.1. Furthersemantics
Intheinterest ofspace,wehaveomittedafew prominentsemantics inthe mainbodyofthissurvey.Inwhat follows wegiverespectivepointerstotheliteratureandhighlightsystemsimplementingthesesemantics.
As shownby Baroni etal.[126] argumentation semantics canbe definedon the basis ofdecomposing an AF intoits strongly connectedcomponents(SCCs).This notonly providesalternative definitionsof some ofthesemantics whichwe havealreadydiscussedinthe paper,butalsoleads tonovelsemantics, forinstancecf2[126] andstage2[127] semantics.
For bothsemantics, ASPencodings[127,133]aswell aslabeling-basedalgorithms [127] havebeenpresented, theformer areintegratedintheASPARTIXsystem.
Moreover, thereisthefamilyofresolution-basedsemantics [128],withtheresolution-basedgroundedsemanticsbeing the mostpopular instance.Different ASP encodingsforresolution-based groundedsemantics are studied in[31] and are incorporatedintheASPARTIXsystem,aswell.
Finally, the unique-status semantics ideal [124] and eager [125] (for a general notion of parametric ideal semantics, see[134])havebeenproposedtoperformaprudentformofreasoningonthesetofpreferredextensionsandsemi-stable extensions,respectively.Acharacterizationintermsoflabelingsforidealandeagersemanticsisgivenin[135]and labeling-basedalgorithmshavebeenimplementedintheArguLabsystem.AlsotheDung-O-Maticsystemallowsforreasoningwith idealandeagersemantics.IntheASP-settingacharacterizationforidealsemanticsisgivenin[30]andisimplementedin theASPARTIXsystem.Regardingotherreduction-basedsystems,ConArgisalsocapableofcomputingtheidealextensionof anAF.
6.2. Furthermethods
Next,webriefly describethree conceptswhichcan beconsidered tobeused ontopofargumentationsystemsas dis-cussedinthissurvey.Thesemethodscanbeseenaspre-processingorsimplificationstepsbeforeactuallyevaluatingabstract argumentationframeworks.
First,theideaofsplittingallows todivideanargumentation framework F in(two)smallerargumentationframeworks F1, F2,such that there are no attacksfrom argumentsin F2 to argumentsin F1 [136,137].Then one can first compute theextensionsof F1 andthenforeachofitsextension E computetheextensionsforaslightlymodifiedversion F2E of F2. TheextensionsofF canthenbeobtainedbycombiningeachextension E ofF1 withtheextensionsoftheframeworks F2E. Thebenefitfromthissplittingapproachcomesfromthefactthat both F1 andF2 aresmallerthantheoriginal AF F and thuscanbeevaluatedfaster(however,intheworstcaseanexponentialnumberofAFs F2E hastobehandled).Theideaof splittingAFs hasalsobeengeneralizedbyallowing asmallnumberofattacksfromargumentsin F2 toargumentsin F1, see[138].Inarecentpaper,LiaoandHuanghaveproposedarelatedmethodtoevaluateonlypartsofa givenframework whenitcomestocredulousorskepticalreasoningproblems[139].
Second,theidentificationofredundantpatternsmightbeusedtosimplifyargumentationframeworksbeforeevaluation.
Thenotionofstrongequivalence[73,140]providesmeanstoidentifyredundantattackswithoutanalyzingtheentire frame-work(an exampleareattacksbetweentwo self-attackingarguments;such attackscanbe safelyremovedformostofthe semantics).Relaxednotionsofstrongequivalencemightbeevenmorebeneficialforthispurpose,see,e.g.,[141,142].
Finally,wementiontheconceptofintertranslatabilitybetweenabstractargumentationsemantics[72].Here,oneis inter-estedintranslationsfromasemantics
σ
toanothersemanticsτ
,i.e.,afunctionTrthattransformsarbitraryargumentation frameworks F such thatσ
(F)=τ
(Tr(F)). If thistranslation function Tr can be computed efficiently we can combineit withanysystemforsemanticsτ
tobuild asystemforσ
.Sotranslationsbetweendifferentsemanticsallowtoexpandthe applicabilityofexistingargumentationsystems.6.3. Furthersystems
In this work we focused on systems that implement the evaluation of semantics on Dung’s abstract argumentation frameworkdirectly.However,thereexistsawiderangeofsystemsthatextendthesecapabilities,inparticularbyadditionally supportinginstantiationofargumentationframeworks.
One approach is based on ASPIC [143], resp. ASPIC+ [50], which instantiates Dung-style frameworks. Arguments are represented asinference trees by applyingstrict and defeasible inference rules. TOAST (TheOnline Argument Structures Tool) [144] isan implementation ofASPIC+ andis availableasweb front-end.16 Theuser-specified knowledgebase, rule set,contrarinessandpreferences areused toconstructan argumentationsystemwhichcan currentlybe evaluatedbased on grounded, preferred, semi-stable and stable semantics. The ASPIC argumentation engine demo17 implements several instantiations ofASPIC andprovidesa webinterface. Againthe usercan specifyaknowledge baseanda rulesetto con-structan argumentationsystemwhichthen canbe evaluated basedongroundedandcredulous preferredsemantics. The CarneadesWebService18iscapable of“argumentconstruction,storage,navigation,querying,evaluation,visualization and interchange” [145].It is basedon theASPIC+ modelofstructured argument butstill preservesthefeatures of the origi-nalversion ofCarneadessystem[51].OntheresultingDung-styleframework itappliesgrounded semantics.Anapproach basedonclassicallogicandargumentinstantiationisshownin[146].Here,argumentsandpossiblecounterargumentsare constructedfromaclassical propositionalknowledgebase.Furthermore,Vispartix19consistsofacollectionofASP encod-ings[147] forobtaining Dung argumentationframeworks froma propositional knowledge base(and a set ofpredefined
One approach is based on ASPIC [143], resp. ASPIC+ [50], which instantiates Dung-style frameworks. Arguments are represented asinference trees by applyingstrict and defeasible inference rules. TOAST (TheOnline Argument Structures Tool) [144] isan implementation ofASPIC+ andis availableasweb front-end.16 Theuser-specified knowledgebase, rule set,contrarinessandpreferences areused toconstructan argumentationsystemwhichcan currentlybe evaluatedbased on grounded, preferred, semi-stable and stable semantics. The ASPIC argumentation engine demo17 implements several instantiations ofASPIC andprovidesa webinterface. Againthe usercan specifyaknowledge baseanda rulesetto con-structan argumentationsystemwhichthen canbe evaluated basedongroundedandcredulous preferredsemantics. The CarneadesWebService18iscapable of“argumentconstruction,storage,navigation,querying,evaluation,visualization and interchange” [145].It is basedon theASPIC+ modelofstructured argument butstill preservesthefeatures of the origi-nalversion ofCarneadessystem[51].OntheresultingDung-styleframework itappliesgrounded semantics.Anapproach basedonclassicallogicandargumentinstantiationisshownin[146].Here,argumentsandpossiblecounterargumentsare constructedfromaclassical propositionalknowledgebase.Furthermore,Vispartix19consistsofacollectionofASP encod-ings[147] forobtaining Dung argumentationframeworks froma propositional knowledge base(and a set ofpredefined