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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

Command Line Interface (org.tweetyproject.cli)

Example code:

no example code available

Resources:

no resources available

Commons (org.tweetyproject.commons)

Example code: Resources:

no resources available

Comparator Library (org.tweetyproject.comparator)

Example code:

no example code available

Resources:

no resources available

Graph Library (org.tweetyproject.graphs)

Example code: Resources:

no resources available

Math (org.tweetyproject.math)

Example code: Resources:

no resources available

Plugin Project (org.tweetyproject.plugin)

Example code:

no example code available

Resources:

no resources available

Logic Libraries

Business Process Modelling (org.tweetyproject.logics.bpm)

Example code: Resources:

Conditional Logic (org.tweetyproject.logics.cl)

Example code: Resources:

Commons Logic (org.tweetyproject.logics.commons)

Example code:

no example code available

Resources:

no resources available

Description Logics (org.tweetyproject.logics.dl)

Example code: Resources:

First-Order-Logic (org.tweetyproject.logics.fol)

Example code: Resources:

Modal Logic Library (org.tweetyproject.logics.ml)

Example code:
  • examples.MlExample.java: Some examples for testing ModalParser and NaiveModalReasoner. Shows how to construct a modal logic knowledge base programmatically and how to query it using the naive reasoner.
  • examples.MlExample2.java: More examples for testing ModalParser and ModalReasoner. Shows how to construct a modal logic knowledge base programmatically and how to query it using the SPASS reasoner.
  • examples.MlExample.java: Some examples for testing ModalParser and NaiveModalReasoner. Shows how to construct a modal logic knowledge base programmatically and how to query it using the naive reasoner.
  • examples.MlExample2.java: More examples for testing ModalParser and ModalReasoner. Shows how to construct a modal logic knowledge base programmatically and how to query it using the SPASS reasoner.
Resources:

Markov Logic Networks Library (org.tweetyproject.logics.mln)

Example code: Resources:

no resources available

Probabilistic Conditional Logic Library (org.tweetyproject.logics.pcl)

Example code: Resources:

no resources available

Petri Nets Library (org.tweetyproject.logics.petri)

Example code:

no example code available

Resources:

no resources available

Propositional Logic (org.tweetyproject.logics.pl)

Example code: Resources:

Quantified Boolean Formulas (org.tweetyproject.logics.qbf)

Example code: Resources:

Relational Conditional Logic Library (org.tweetyproject.logics.rcl)

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

no resources available

Reiter's Default Logic Library (org.tweetyproject.logics.rdl)

Example code: Resources:

Relational Probabilistic Conditional Logic Library (org.tweetyproject.logics.rpcl)

Example code: Resources:

Translators Library (org.tweetyproject.logics.translators)

Example code:

no example code available

Resources:

Logic Programming Libraries

ASP Library (org.tweetyproject.lp.asp)

Example code: Resources:

ASP Belief Dynamics (org.tweetyproject.lp.asp.beliefdynamics)

Example code:

no example code available

Resources:

no resources available

Nested Logic Programs (org.tweetyproject.lp.nlp)

Example code:

no example code available

Resources:

no resources available

Argumentation Libraries

ABA Library (org.tweetyproject.arg.aba)

Example code:
  • examples.AbaExample.java: Shows some simple code for working with ABA, including how to parse an ABA file and how to ask queries.
  • examples.AbaExample.java: Shows some simple code for working with ABA, including how to parse an ABA file and how to ask queries.
Resources:

ADF Library (org.tweetyproject.arg.adf)

Example code: Resources:

ASPIC Library (org.tweetyproject.arg.aspic)

Example code: Resources:

Bipolar Argumentation Library (org.tweetyproject.arg.bipolar)

Example code: Resources:

no resources available

Deductive Argumentation Library (org.tweetyproject.arg.deductive)

Example code: Resources:

no resources available

Defeasible Logic Programming Library (org.tweetyproject.arg.delp)

Example code: Resources:

Dung Argumentation Library (org.tweetyproject.arg.dung)

Example code: Resources:

Logic Programming Argumentation Library (org.tweetyproject.arg.lp)

Example code:

no example code available

Resources:

no resources available

Probabilistic Argumentation Library (org.tweetyproject.arg.prob)

Example code: Resources:

no resources available

Ranking Semantics for Argumentation Library (org.tweetyproject.arg.rankings)

Example code:
  • examples.CounterTransitivityReasonerExample.java
  • examples.IteratedGradedDefenseReasonerExample.java: Example code for using the iterated graded semantics from [Grossi, Modgil. On the Graded Acceptability of Arguments. IJCAI 2015].
  • examples.ProbabilisticRankingReasonerExample.java: Example code for using the probabilistic ranking reasoner based on the ideas from [Thimm, Cerutti, Rienstra. Probabilistic Graded Semantics. COMMA 2018].
  • examples.RankingPostulatesExample.java: Example code for evaluating ranking semantics in regard to postulates. Each postulate represents a single property that characterizes how the semantics ranks arguments.
  • examples.RankingSemanticsExample.java: Example code for the following ranking semantics:
    - Categorizer [Besnard, Hunter. A logic-based theory of deductive arguments. 2001]
    - Burden-Based [Amgoud, Ben-Naim. Ranking-based semantics for argumentation frameworks. 2013]
    - Discussion-Based [Amgoud, Ben-Naim. Ranking-based semantics for argumentation frameworks. 2013]
    - Tuples [Cayrol, Lagasquie-Schiex. Graduality in argumentation. 2005]
    - Strategy-Based [Matt, Toni. A game-theoretic measure of argument strength for abstract argumentation. JELIA 2008]
    - Social Abstract Argumentation with simple product semantics [Bonzon, Delobelle, Konieczny, Maudet. A Comparative Study of Ranking-Based Semantics for Abstract Argumentation. AAAI 2016]
    - Iterated Graded Defense [Grossi, Modgil. On the Graded Acceptability of Arguments. IJCAI 2015]
    - Probabilistic Graded Semantics [Thimm, Cerutti, Rienstra. Probabilistic Graded Semantics. COMMA 2018].
  • examples.RankingSemanticsExample2.java: Example code for even more ranking semantics:
    - Counting Semantics [Pu, Zhang, G.Luo, J.Luo. Attacker and Defender Counting Approach for Abstract Argumentation. CoRR 2015].
    - The three variations of the Propagation Semantics [Delobelle. Ranking-based Semantics for Abstract Argumentation. Thesis, 2017])
  • examples.SerialisableRankingReasonerExample.java
  • examples.CounterTransitivityReasonerExample.java
  • examples.IteratedGradedDefenseReasonerExample.java: Example code for using the iterated graded semantics from [Grossi, Modgil. On the Graded Acceptability of Arguments. IJCAI 2015].
  • examples.ProbabilisticRankingReasonerExample.java: Example code for using the probabilistic ranking reasoner based on the ideas from [Thimm, Cerutti, Rienstra. Probabilistic Graded Semantics. COMMA 2018].
  • examples.RankingPostulatesExample.java: Example code for evaluating ranking semantics in regard to postulates. Each postulate represents a single property that characterizes how the semantics ranks arguments.
  • examples.RankingSemanticsExample.java: Example code for the following ranking semantics:
    - Categorizer [Besnard, Hunter. A logic-based theory of deductive arguments. 2001]
    - Burden-Based [Amgoud, Ben-Naim. Ranking-based semantics for argumentation frameworks. 2013]
    - Discussion-Based [Amgoud, Ben-Naim. Ranking-based semantics for argumentation frameworks. 2013]
    - Tuples [Cayrol, Lagasquie-Schiex. Graduality in argumentation. 2005]
    - Strategy-Based [Matt, Toni. A game-theoretic measure of argument strength for abstract argumentation. JELIA 2008]
    - Social Abstract Argumentation with simple product semantics [Bonzon, Delobelle, Konieczny, Maudet. A Comparative Study of Ranking-Based Semantics for Abstract Argumentation. AAAI 2016]
    - Iterated Graded Defense [Grossi, Modgil. On the Graded Acceptability of Arguments. IJCAI 2015]
    - Probabilistic Graded Semantics [Thimm, Cerutti, Rienstra. Probabilistic Graded Semantics. COMMA 2018].
  • examples.RankingSemanticsExample2.java: Example code for even more ranking semantics:
    - Counting Semantics [Pu, Zhang, G.Luo, J.Luo. Attacker and Defender Counting Approach for Abstract Argumentation. CoRR 2015].
    - The three variations of the Propagation Semantics [Delobelle. Ranking-based Semantics for Abstract Argumentation. Thesis, 2017])
  • examples.SerialisableRankingReasonerExample.java
Resources:

Structured Argumentation Frameworks Library (org.tweetyproject.arg.saf)

Example code:

no example code available

Resources:

no resources available

SetAFs (org.tweetyproject.arg.setaf)

Example code: Resources:

Social Abstract Argumentation Library (org.tweetyproject.arg.social)

Example code: Resources:

no resources available

Agent Libraries

Agents Library (org.tweetyproject.agents)

Example code:

no example code available

Resources:

no resources available

Dialogue Systems Library (org.tweetyproject.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: Main class for empirical evaluation in [Hunter, Thimm. 2015, to appear]. 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.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: Main class for empirical evaluation in [Hunter, Thimm. 2015, to appear]. 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

Other Libraries

Action and Change (org.tweetyproject.action)

Example code:

no example code available

Resources:

Belief Dynamics Library (org.tweetyproject.beliefdynamics)

Example code: Resources:

no resources available

Machine Learning Library (org.tweetyproject.machinelearning)

Example code: Resources:

no resources available

Preferences Library (org.tweetyproject.preferences)

Example code:

no example code available

Resources:

SAT Library (org.tweetyproject.sat)

Example code:

no example code available

Resources:

Web Services (org.tweetyproject.web)

Example code:

no example code available

Resources:

no resources available




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Last updated 31.01.2023, Matthias Thimm | Terms