Class CounterTransitivityReasoner
java.lang.Object
org.tweetyproject.arg.rankings.reasoner.AbstractRankingReasoner<LatticePartialOrder<Argument,DungTheory>>
org.tweetyproject.arg.rankings.reasoner.CounterTransitivityReasoner
- All Implemented Interfaces:
ModelProvider<Argument,
,DungTheory, LatticePartialOrder<Argument, DungTheory>> PostulateEvaluatable<Argument>
public class CounterTransitivityReasoner
extends AbstractRankingReasoner<LatticePartialOrder<Argument,DungTheory>>
This class implements the argument ranking approach of [Pu, Luo,
Ranking Arguments based on Counter-Transitivity 2017].
- Author:
- Sebastian Franke
-
Nested Class Summary
Modifier and TypeClassDescriptionstatic enum
The solver used to determine the ranking of arguments. -
Constructor Summary
ConstructorDescriptionCounterTransitivityReasoner
(CounterTransitivityReasoner.solver sol, LatticePartialOrder<Argument, DungTheory> rank) Constructor -
Method Summary
Modifier and TypeMethodDescriptionorders arguments after the amount of attackers they have.ranks arguments according to the cardinality function.getModel
(DungTheory bbase) Returns a single (dedicated) model of the given belief base.getModels
(DungTheory bbase) Returns a characterizing model of the given belief basecalculates the greatest fix point.boolean
natively installedranks arguments according to a given ranking.ranks arguments according to the quality function.only ranks two arguments if one is better according to quality and cardinality
-
Constructor Details
-
CounterTransitivityReasoner
public CounterTransitivityReasoner(CounterTransitivityReasoner.solver sol, LatticePartialOrder<Argument, DungTheory> rank) Constructor- Parameters:
sol
- solverrank
- the rank
-
-
Method Details
-
getModels
Description copied from interface:ModelProvider
Returns a characterizing model of the given belief base- Parameters:
bbase
- some belief base- Returns:
- the (selected) models of the belief base
-
getModel
Description copied from interface:ModelProvider
Returns a single (dedicated) model of the given belief base. If the implemented method allows for more than one dedicated model, the selection may be non-deterministic.- Parameters:
bbase
- some belief base- Returns:
- a selected model of the belief base.
-
cardinality
orders arguments after the amount of attackers they have. The less attackers, the higher the rank- Parameters:
af
- the af- Returns:
- the cardinality
-
quality
public LatticePartialOrder<Argument,DungTheory> quality(DungTheory af, LatticePartialOrder<Argument, DungTheory> ra) ranks arguments according to a given ranking. It decides the highest ranked attacker of each argument wrt the underlying ranking and then ranks them after their best attacker- Parameters:
af
- the afra
- the ra- Returns:
- the quality
-
qualityFirst
public LatticePartialOrder<Argument,DungTheory> qualityFirst(DungTheory af, LatticePartialOrder<Argument, DungTheory> ra) ranks arguments according to the quality function. If 2 arguments have the same avlue according to quality, the decsision is left to cardinality- Parameters:
af
- the afra
- the ra- Returns:
- quality first
-
cardinalityFirst
public LatticePartialOrder<Argument,DungTheory> cardinalityFirst(DungTheory af, LatticePartialOrder<Argument, DungTheory> ra) ranks arguments according to the cardinality function. If 2 arguments have the same value according to cardinality, the decision is left to quality- Parameters:
af
- the afra
- the ra- Returns:
- cardinality first
-
gfpCardinality
calculates the greatest fix point. First the quality is computed based on a ranking that only ranks unattacked arguments higher than the rest. Based on this ranking a cardinality first ranking is constructed. Based on this new ranking a quality ranking is constructed. This process is repeated until two consecutive iterations of cardinality first reach the same conclusion- Parameters:
af
- the af- Returns:
- the gfpcardinality
-
simpleDominance
public LatticePartialOrder<Argument,DungTheory> simpleDominance(DungTheory af, LatticePartialOrder<Argument, DungTheory> ra) only ranks two arguments if one is better according to quality and cardinality- Parameters:
af
- the afra
- the ra- Returns:
- the simple dominance
-
isInstalled
public boolean isInstalled()natively installed- Specified by:
isInstalled
in classAbstractRankingReasoner<LatticePartialOrder<Argument,
DungTheory>> - Returns:
- is installed status
-