TweetyProject

A comprehensive collection of Java libraries for logical aspects of artificial intelligence and knowledge representation

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Example code and resources

Most libraries have an examples package that contains various example code snippets that show the functionality of the library. In addition, the resources folder contains examplary instance files that can be parsed by the corresponding parser into the classes of the library.

Below is an up-to-date list of available examples and instance files.

• General Libraries
  • Commons (net.sf.tweety.commons)
  • Plugin (net.sf.tweety.plugin)
  • Command Line Interface (net.sf.tweety.cli)
  • Math (net.sf.tweety.math)
  • Graphs (net.sf.tweety.graphs)
• Logic Libraries
  • Logic Commons (net.sf.tweety.logics.commons)
  • Propositional Logic (net.sf.tweety.logics.pl)
  • First-Order Logic (net.sf.tweety.logics.fol)
  • Conditional Logic (net.sf.tweety.logics.cl)
  • Relational Conditional Logic (net.sf.tweety.logics.rcl)
  • Probabilistic Conditional Logic (net.sf.tweety.logics.pcl)
  • Relational Probabilistic Conditional Logic (net.sf.tweety.logics.rpcl)
  • Reiter's Default Logic (net.sf.tweety.logics.rdl)
  • Modal Logic (net.sf.tweety.logics.ml)
  • Markov Logic Networks (net.sf.tweety.logics.mln)
  • Description Logic (net.sf.tweety.logics.dl)
  • Logic Translators (net.sf.tweety.logics.translators)
• Logic Programming Libraries
  • Answer Set Programming (net.sf.tweety.lp.asp)
  • Dynamics in Answer Set Programming (net.sf.tweety.lp.asp.beliefdynamics)
  • Nested Logic Programs (net.sf.tweety.lp.nlp)
• Argumentation Libraries
  • Abstract Argumentation (net.sf.tweety.arg.dung)
  • ABA (net.sf.tweety.arg.aba)
  • Abstract Dialectical Frameworks (net.sf.tweety.arg.adf)
  • ASPIC+ (net.sf.tweety.arg.aspic)
  • Deductive Argumentation (net.sf.tweety.arg.deductive)
  • Social Abstract Argumentation (net.sf.tweety.arg.social)
  • Structured Argumentation (net.sf.tweety.arg.saf)
  • Defeasible Logic Programming (net.sf.tweety.arg.delp)
  • Logic Programming Argumentation (net.sf.tweety.arg.lp)
  • Probabilistic Argumentation (net.sf.tweety.arg.prob)
• Agent Libraries
  • Agents (net.sf.tweety.agents)
  • Dialogues (net.sf.tweety.agents.dialogues)
• Other Libraries
  • Action and Change (net.sf.tweety.action)
  • Belief Dynamics (net.sf.tweety.beliefdynamics)
  • Machine Learning (net.sf.tweety.machinelearning)
  • Preferences (net.sf.tweety.preferences)
  • Web (net.sf.tweety.web)

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General Libraries

Commons (net.sf.tweety.commons)

Example code:

• examples.SubsetIteratorExample.java: Shows how to use a subset iterator.

Resources: no resources available

Plugin (net.sf.tweety.plugin)

no example code available

Command Line Interface (net.sf.tweety.cli)

no example code available

Math (net.sf.tweety.math)

no example code available

Graphs (net.sf.tweety.graphs)

Example code:

• examples.GraphExample.java: Shows how to construct graphs programmatically.

Resources: no resources available

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Logic Libraries

Logic Commons (net.sf.tweety.logics.commons)

no example code available

Propositional Logic (net.sf.tweety.logics.pl)

Example code:

• examples.ContensionExample.java: Example code illustrating the contension inconsistency measure.
• examples.DfInconsistencyMeasureExample.java: Example code illustrating the Df inconsistency measure.
• examples.DSumMeasureExample.java: Example code illustrating distance-based inconsistency measures.
• examples.FuzzyMeasureExample.java: Example code illustrating fuzzy logic-based inconsistency measures.
• examples.ImPostulateEvaluationExample.java: Example code illustrating automatic postulate evaluation of inconsistency measures.
• examples.LingelingExample.java: Example code illustrating the use of the SAT solver Lingeling.
• examples.MaMeasureExample.java: Example code illustrating the Ma inconsistency measure.
• examples.McscInconsistencyMeasureExample.java: Example code illustrating the MCSC inconsistency measure.
• examples.MinimalInconsistentSubsetExample.java: Example code illustrating the use of MUS enumerators.
• examples.MusExample.java: Example code illustrating the use of MUS enumerators.
• examples.PmMeasureExample.java: Example code illustrating the Pm inconsistency measure.
• examples.StreamInconsistencyEvaluationExample.java: Illustrates stream-based inconsistency measurement.
• examples.StreamInconsistencyEvaluationExample2.java: Illustrates stream-based inconsistency measurement.
• examples.SyntacticEnumeratingPlBeliefSetSamplerExample.java: Illustrates the use of the belief base enumerators.
• examples.SyntacticRandomPlBeliefSetSamplerExample.java: Illustrates the use of the belief base enumerators.

Resources:

• resources.dimacs_ex1.cnf: Propositional knowledge base in CNF that can be parsed using parser.DimacsParser.
• resources.dimacs_ex2.cnf: Propositional knowledge base in CNF that can be parsed using parser.DimacsParser.
• resources.dimacs_ex3.cnf: Propositional knowledge base in CNF that can be parsed using parser.DimacsParser.
• resources.dimacs_ex4.cnf: Propositional knowledge base in CNF that can be parsed using parser.DimacsParser.
• resources.dimacs_ex5.cnf: Propositional knowledge base in CNF that can be parsed using parser.DimacsParser.
• resources.examplebeliefbase.proplogic: Propositional knowledge base that can be parsed using parser.PlParser.

First-Order Logic (net.sf.tweety.logics.fol)

Example code:

• examples.FolExample.java: Some examples for using FolParser and provers.

Resources:

• resources.examplebeliefbase.fologic: First-order logic knowledge base that can be parsed using parser.FolParser.

Conditional Logic (net.sf.tweety.logics.cl)

Example code:

• examples.CReasonerExample.java: Shows how to construct a conditional logic knowledge base programmatically and how to query it using the C-reasoner.
• examples.ReasonerExample.java: Compares reasoning with different reasoners.

Resources: no resources available

Relational Conditional Logic (net.sf.tweety.logics.rcl)

Example code:

• examples.RclExample.java: Example code illustrating the use of working with relational conditionals and using c reasoning.

Resources: no resources available

Probabilistic Conditional Logic (net.sf.tweety.logics.pcl)

Example code:

• examples.AnalysisExample.java: Example code illustrating the use of inconsistency measures and repairing approaches.
• examples.RepairExample.java: Example code illustrating the use of repairing approaches.

Resources: no resources available

Relational Probabilistic Conditional Logic (net.sf.tweety.logics.rpcl)

Example code:

• examples.RpclMeReasonerExample.java: Example code illustrating relational probabilistic conditional logic and reasoning with it.
• examples.RpclMeReasonerExample2.java: Example code illustrating relational probabilistic conditional logic and reasoning with it.

Resources:

• resources.cold.rpcl: A relational probabilistic conditional knowledge base that can be parsed using parser.RpclParser.
• resources.elephants.rpcl: A relational probabilistic conditional knowledge base that can be parsed using parser.RpclParser.
• resources.penguins.rpcl: A relational probabilistic conditional knowledge base that can be parsed using parser.RpclParser.

Reiter's Default Logic (net.sf.tweety.logics.rdl)

Example code:

• examples.RdlExample.java: Example code illustrating Reiter's default logic.

Resources:

• resources.example_default_theory.txt: A default theory that can be parsed using parser.RdlParser.
• resources.simple_default_theory.txt: A default theory that can be parsed using parser.RdlParser.

Modal Logic (net.sf.tweety.logics.ml)

Example code:

• examples.MlExample.java: Shows how to construct a modal logic knowledge base programmatically and how to query it using the naive reasoner.
• examples.MlExample2.java: Shows how to construct a modal logic knowledge base programmatically and how to query it using the SPASS reasoner.

Resources:

• resources.examplebeliefbase.mlogic: A modal logic theory that can be parsed using parser.ModalParser.

Markov Logic Networks (net.sf.tweety.logics.mln)

Example code:

• examples.AlchemyExample.java: Example code illustrating the use of the Alchemy reasoner.
• examples.ApproximationExample.java: Example code illustrating the use of the sampling-based MLN reasoner.
• examples.MlnExample.java: Shows how MLNs can be constructed programmatically and shows how coherence measures can be used.
• examples.MlnExample2.java: Gives further examples on how MLNs can be constructed programmatically and how coherence measures can be used

Resources: no resources available

Description Logic (net.sf.tweety.logics.dl)

Example code:

• examples.DlExample.java: Examples for using the description logic syntax classes and parser.

Resources: no resources available

Logic Translators (net.sf.tweety.logics.translators)

no example code available

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Logic Programming Libraries

Answer Set Programming (net.sf.tweety.lp.asp)

Example code:

• examples.ASPCore2ParserExample.java: Examples for parsing simple ELP programs and for using Clingo to solve them.

Resources:

• resources.Eiter2002_Ex1_Part1.dl: An answer set program that can be parsed using parser.ASPParser.
• resources.Eiter2002_Ex1_Part2.dl: An answer set program that can be parsed using parser.ASPParser.
• resources.Eiter2002_Ex1_Part3.dl: An answer set program that can be parsed using parser.ASPParser.
• resources.Eiter2002_Ex1_Part4.dl: An answer set program that can be parsed using parser.ASPParser.
• resources.Eiter2002_Ex2_Part1.dl: An answer set program that can be parsed using parser.ASPParser.
• resources.Eiter2002_Ex2_Part2.dl: An answer set program that can be parsed using parser.ASPParser.
• resources.Eiter2002_Ex2_Part3.dl: An answer set program that can be parsed using parser.ASPParser.
• resources.ex1.asp: An answer set program that can be parsed using parser.ASPParser.
• resources.ex2.asp: An answer set program that can be parsed using parser.ASPParser.
• resources.ex3.asp: An answer set program that can be parsed using parser.ASPParser.
• resources.ex4.asp: An answer set program that can be parsed using parser.ASPParser.
• resources.Krue2008_Ex1_Part1.dl: An answer set program that can be parsed using parser.ASPParser.
• resources.Krue2008_Ex1_Part1.dl: An answer set program that can be parsed using parser.ASPParser.
• resources.Krue2008_Ex1_Part1.dl: An answer set program that can be parsed using parser.ASPParser.
• resources.Krue2008_Ex1_Part1.dl: An answer set program that can be parsed using parser.ASPParser.
• resources.Krue2008_Ex1_Part1.dl: An answer set program that can be parsed using parser.ASPParser.
• resources.Krue2008_Ex1_Part1.dl: An answer set program that can be parsed using parser.ASPParser.

Dynamics in Answer Set Programming (net.sf.tweety.lp.asp.beliefdynamics)

no example code available

Nested Logic Programs (net.sf.tweety.lp.nlp)

no example code available

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Argumentation Libraries

Abstract Argumentation (net.sf.tweety.arg.dung)

Example code:

• examples.CF2Example.java: Shows how to construct an abstract argumentation framework programmatically and how to reason with it using CF2 semantics.
• examples.DivisionExample.java: Example code for working with divisions.
• examples.GrossiModgilReasonerExample.java: Example code for using graded semantics by Grossi/Modgil.
• examples.StratifiedLabelingExample.java: Example code for using stratified labelings by Thimm/Kern-Isberner.

Resources:

• resources.ex1.apx: Abstract argumentation framework in APX syntax, can be parsed using parser.ApxParser.
• resources.ex1.tgf: Abstract argumentation framework in TGF syntax, can be parsed using parser.TgfParser.
• resources.ex2.apx: Abstract argumentation framework in APX syntax, can be parsed using parser.ApxParser.
• resources.ex2.tgf: Abstract argumentation framework in TGF syntax, can be parsed using parser.TgfParser.
• resources.ex3.apx: Abstract argumentation framework in APX syntax, can be parsed using parser.ApxParser.
• resources.ex3.tgf: Abstract argumentation framework in TGF syntax, can be parsed using parser.TgfParser.

ABA (net.sf.tweety.arg.aba)

Example code:

• examples.AbaExample.java: Shows how to parse an ABA file and how to ask queries.

Resources:

• resources.example1.aba: ABA knowledge base that can be parsed using parser.ABAparser.
• resources.example2.aba: ABA knowledge base that can be parsed using parser.ABAparser.
• resources.example3.aba: ABA knowledge base that can be parsed using parser.ABAparser.
• resources.example4.aba: ABA knowledge base that can be parsed using parser.ABAparser.
• resources.example5.aba: ABA knowledge base that can be parsed using parser.ABAparser.
• resources.example11.aba: ABA knowledge base that can be parsed using parser.ABAparser.

Abstract Dialectical Frameworks (net.sf.tweety.arg.adf)

no example code available

ASPIC+ (net.sf.tweety.arg.aspic)

Example code:

• examples.AspicExample.java: Shows how to construct an ASPIC theory programmatically.
• examples.AspicExample2.java: Shows how to parse an ASPIC file and ask queries.
• examples.AspicGeneratorExample.java: Exemplary code illustrating the use of the ASPIC theory generator. Furthermore this code show a small performance comparison between the naive ASPIC reasoner and the module based reasoner.
• examples.AspicGeneratorExample2.java: This code shows the use of the ASPIC theory generator. It generates some random ASPIC theories, constructs the corresponding AF graphs, and writes them to a specific folder.
• examples.AspicGeneratorExample3.java: This code shows the use of the ASPIC theory generator. It generates some random ASPIC theories with some parameter combinations and writes them to disk.
• examples.DirectionalReasonerTestjava: Test runtime of module-based vs. directional reasoners. Also checks if they give the same answers.

Resources:

• resources.ex1.aspic: ASPIC knowledge base that can be parsed using parser.AspicParser.
• resources.ex2.aspic: ASPIC knowledge base that can be parsed using parser.AspicParser.
• resources.ex3.aspic: ASPIC knowledge base that can be parsed using parser.AspicParser.
• resources.ex4.aspic: ASPIC knowledge base that can be parsed using parser.AspicParser.

Deductive Argumentation (net.sf.tweety.arg.deductive)

Example code:

• examples.DeductiveExample.java: Shows how to construct and query a deductive knowledge base.
• examples.SimplePlLogicExample.java: Example code for simple logic argumentation.

Resources: no resources available

Social Abstract Argumentation (net.sf.tweety.arg.social)

Example code:

• examples.SafExample.java: Example code for using social abstract argumentation.

Resources: no resources available

Structured Argumentation (net.sf.tweety.arg.saf)

no example code available

Defeasible Logic Programming (net.sf.tweety.arg.delp)

Example code:

• examples.DeLPExample.java: Shows how to parse and query a DeLP program.

Resources:

• resources.birds.txt: DeLP program that can be parsed using parser.DelpParser.
• resources.birds2.txt: DeLP program that can be parsed using parser.DelpParser.
• resources.counterarg.txt: DeLP program that can be parsed using parser.DelpParser.
• resources.dtree.txt: DeLP program that can be parsed using parser.DelpParser.
• resources.hobbes.txt: DeLP program that can be parsed using parser.DelpParser.
• resources.nixon.txt: DeLP program that can be parsed using parser.DelpParser.
• resources.stocks.txt: DeLP program that can be parsed using parser.DelpParser.

Logic Programming Argumentation (net.sf.tweety.arg.lp)

no example code available

Probabilistic Argumentation (net.sf.tweety.arg.prob)

Example code:

• examples.LotteryExample.java: Example code for working with lotteries in probabilistic abstract argumentation.
• examples.PAInconsistencyMeasureExample.java: Example code for the PAInconsistencyMeasure.
• examples.ProbabilisticRankingReasonerExample.java: Example code for using graded semantics reasoner based on the ideas from [Thimm, Cerutti, Rienstra; 2018].
• examples.SubgraphProbExample.java: Example code for showing how to work with subgraph probability distributions and updates.

Resources: no resources available

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Agent Libraries

Agents (net.sf.tweety.agents)

no example code available

Dialogues (net.sf.tweety.agents.dialogues)

Example code:

• examples.GroundedTest.java: Shows how a simulation of a multi-agent system can be set up. It defines a dialogue game between different agents with varying complexity of their opponent models.
• examples.GroundedTest2.java: Shows how a simulation of a multi-agent system can be set up. It defines a dialogue game between different agents with varying complexity of their opponent models.
• examples.LotteryDialogueTest.java: Shows how a simulation of a multi-agent system can be set up. It defines a dialogue game between different agents, in particular one based on an action selection strategy using lotteries.
• examples.LotteryDialogueTest2.java: Shows how a simulation of a multi-agent system can be set up. It defines a dialogue game between different agents, in particular one based on an action selection strategy using lotteries.

Resources: no resources available

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Other Libraries

Action and Change (net.sf.tweety.action)

Example code: no example code available

Resources:

• resources.conditioner.desc: An action description that can be parsed using description.parser.CParser.
• resources.monkey.desc: An action description that can be parsed using description.parser.CParser.
• resources.monkey.query: An action query that can be parsed using query.parser.ActionQueryParser.
• resources.turkey.desc: An action description that can be parsed using description.parser.CParser.
• resources.water.query: An action query that can be parsed using query.parser.ActionQueryParser.

Belief Dynamics (net.sf.tweety.beliefdynamics)

Example code:

• examples.AbstractArgumentationExample.java: Example code for applying belief dynamics on abstract argumentation frameworks.
• examples.CrMasExample.java: Example code on using belief operators in multi-agent settings.

Resources: no resources available

Machine Learning (net.sf.tweety.machinelearning)

Example code:

• examples.SvmExample.java: Illustrates the use of support vector machine learning.

Resources: no resources available

Preferences (net.sf.tweety.preferences)

Example code: no example code available

Resources:

• resources.TestA.po: Preference order that can be parsed using parser.POParser.
• resources.TestB.po: Preference order that can be parsed using parser.POParser.
• resources.TestC.po: Preference order that can be parsed using parser.POParser.
• resources.TestD.po: Preference order that can be parsed using parser.POParser.
• resources.TestE.po: Preference order that can be parsed using parser.POParser.

Web (net.sf.tweety.web)

no example code available

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Last updated 07.08.2018, Matthias Thimm | Terms