Commonsense Reasoning and Argumentation 14/15 HC 12 Dynamics of Argumentation (1) Henry Prakken March 23, 2015.

Slides:



Advertisements
Similar presentations
The behavior of SAT solvers in model checking applications K. L. McMillan Cadence Berkeley Labs.
Advertisements

Reflexive example: AB = AB Symmetric example: AB = BA
On norms for the dynamics of argumentative interaction: argumentation as a game Henry Prakken Amsterdam January 18, 2010.
Equivalence Relations
Argumentation Based on the material due to P. M. Dung, R.A. Kowalski et al.
Commonsense Reasoning and Argumentation 14/15 HC 8 Structured argumentation (1) Henry Prakken March 2, 2015.
Computational Models for Argumentation in MAS
Commonsense Reasoning and Argumentation 14/15 HC 9 Structured argumentation (2) Henry Prakken March 4, 2015.
1 In this lecture  Number Theory ● Rational numbers ● Divisibility  Proofs ● Direct proofs (cont.) ● Common mistakes in proofs ● Disproof by counterexample.
Commonsense Reasoning and Argumentation 14/15 HC 10: Structured argumentation (3) Henry Prakken 16 March 2015.
Legal Argumentation 2 Henry Prakken March 28, 2013.
Argumentation Logics Lecture 5: Argumentation with structured arguments (1) argument structure Henry Prakken Chongqing June 2, 2010.
Commonsense Reasoning and Argumentation 14/15 HC 15: Concluding remarks Henry Prakken 1 April 2015.
Argumentation Logics Lecture 1: Introduction Henry Prakken Chongqing May 26, 2010.
Argumentation Logics Lecture 7: Argumentation with structured arguments (3) Rationality postulates, Self-defeat Henry Prakken Chongqing June 4, 2010.
Some problems with modelling preferences in abstract argumentation Henry Prakken Luxemburg 2 April 2012.
Commonsense Reasoning and Argumentation 14/15 HC 13: Dialogue Systems for Argumentation (1) Henry Prakken 25 March 2015.
Basic Properties of Relations
Argumentation in Artificial Intelligence Henry Prakken Lissabon, Portugal December 11, 2009.
20081COMMA08 – Toulouse, May 2008 The Computational Complexity of Ideal Semantics I Abstract Argumentation Frameworks Paul E. Dunne Dept. Of Computer Science.
2.3 Matrix Inverses. Numerical equivalent How would we solve for x in: ax = b ? –a -1 a x = a -1 b –x=a -1 b since a -1 a = 1 and 1x = x We use the same.
Argumentation Logics Lecture 6: Argumentation with structured arguments (2) Attack, defeat, preferences Henry Prakken Chongqing June 3, 2010.
Argumentation Henry Prakken SIKS Basic Course Learning and Reasoning May 26 th, 2009.
Figure 1. Illustration of Ladha’s Study 0q0q 120 b 150 a a m Note: c 1 is the cut point on the first roll call, regardless if legislators adopt.
Argumentation Logics Lecture 7: Argumentation with structured arguments (3) Henry Prakken Chongqing June 4, 2010.
Argumentation Logics Lecture 6: Argumentation with structured arguments (2) Attack, defeat, preferences Henry Prakken Chongqing June 3, 2010.
Argumentation Logics Lecture 3: Abstract argumentation semantics (3) Henry Prakken Chongqing May 28, 2010.
Argumentation Logics Lecture 4: Games for abstract argumentation Henry Prakken Chongqing June 1, 2010.
Argumentation Logics Lecture 1: Introduction Henry Prakken Chongqing May 26, 2010.
ECE 667 Synthesis and Verification of Digital Systems
1 Set Theory. 2 Set Properties Commutative Laws: Associative Laws: Distributive Laws:
Argumentation Logics Lecture 5: Argumentation with structured arguments (1) argument structure Henry Prakken Chongqing June 2, 2010.
1 Set Theory. Notation S={a, b, c} refers to the set whose elements are a, b and c. a  S means “a is an element of set S”. d  S means “d is not an element.
Henry Prakken August 23, 2013 NorMas 2013 Argumentation about Norms.
Relations Chapter 9.
Week 8 - Wednesday.  What did we talk about last time?  Cardinality  Countability  Relations.
Equational Reasoning Math Foundations of Computer Science.
Math 3121 Abstract Algebra I Lecture 3 Sections 2-4: Binary Operations, Definition of Group.
Introduction to formal models of argumentation
Conditional Statements CS 2312, Discrete Structures II Poorvi L. Vora, GW.
Chapter 9. Chapter Summary Relations and Their Properties n-ary Relations and Their Applications (not currently included in overheads) Representing Relations.
Accessible Set Systems Andreas Klappenecker. Matroid Let S be a finite set, and F a nonempty family of subsets of S, that is, F  P(S). We call (S,F)
Balanced Trees (AVL and RedBlack). Binary Search Trees Optimal Behavior ▫ O(log 2 N) – perfectly balanced tree (e.g. complete tree with all levels filled)
Advanced Topics in Propositional Logic Chapter 17 Language, Proof and Logic.
Chapter 2 Section 5. Objective  Students will make a connection between reasoning in Algebra and reasoning in Geometry.
Commonsense Reasoning and Argumentation 14/15 HC 14: Dialogue systems for argumentation (2) Henry Prakken 30 March 2015.
1 Lecture 2 Equivalence Relations Reading: Epp Chp 10.3.
Chap 15. Agreement. Problem Processes need to agree on a single bit No link failures A process can fail by crashing (no malicious behavior) Messages take.
Chapter 9. Chapter Summary Relations and Their Properties n-ary Relations and Their Applications (not currently included in overheads) Representing Relations.
22/07/11IJCAI 2011 Barcelona Relating the Semantics of Abstract Dialectical Frameworks and Standard AFs Gerd Brewka (II, Leipzig) Paul E. Dunne (DCS, Liverpool)
Section 7.5 Equivalence Relations Longin Jan Latecki Temple University, Philadelphia
1 Reasoning with Infinite stable models Piero A. Bonatti presented by Axel Polleres (IJCAI 2001,
Some examples for identity matrixes are I 1 =, I 2 =, I 3 = … Let’s analyze the multiplication of any matrix with identity matrix. = We can conclude that.
Copyright © Cengage Learning. All rights reserved. CHAPTER 8 RELATIONS.
8.5 Equivalence Relations
1 You Never Escape Your… Relations EQUIVALENCE RELATION Presented by K.Senguttuvan, PGT Kendriya Vidyalaya, Gachibowli, Hyderabad. 2.
Week 8 - Wednesday.  What did we talk about last time?  Relations  Properties of relations  Reflexive  Symmetric  Transitive.
Argumentation Logics Lecture 2: Abstract argumentation grounded and stable semantics Henry Prakken Chongqing May 27, 2010.
The Relation Induced by a Partition
Set Theory.
Argumentation pour le raisonnement pratique
Dung-style Argumentation and AGM-style Belief Revision
Henry Prakken COMMA 2016 Berlin-Potsdam September 15th, 2016
2.1 Properties of Real Numbers
Henry Prakken February 23, 2018
Ways to Attack an Argument
FIELD.
Based on the material due to P. M. Dung, R.A. Kowalski et al.
Henry Prakken Chongqing May 27, 2010
A Recursive Approach to Argumentation: Motivation and Perspectives
Presentation transcript:

Commonsense Reasoning and Argumentation 14/15 HC 12 Dynamics of Argumentation (1) Henry Prakken March 23, 2015

Overview Extended argumentation frameworks Arguing about defeat relations Expanding abstract argumentation frameworks Resolving abstract argumentation frameworks

Dynamics in abstract argumentation Adding or deleting: Attacks/defeats Arguments (plus induced attacks/defeats) 3

Arguing about defeat relations Standards for determining defeat relations are often: Domain-specific Defeasible and conflicting So determining these standards is argumentation! Recently Modgil (AIJ 2009) has extended Dung’s abstract approach Arguments can also attack attack relations

CB Modgil 2009 Will it rain in Calcutta? BBC says rain CNN says sun

C T B Modgil 2009 Will it rain in Calcutta? BBC says rain CNN says sun Trust BBC more than CNN

C T B S Modgil 2009 Will it rain in Calcutta? BBC says rain CNN says sun Trust BBC more than CNN Stats say CNN better than BBC

C T B S Modgil 2009 Will it rain in Calcutta? BBC says rain CNN says sun Trust BBC more than CNN Stats say CNN better than BBC R Stats more rational than trust

Expanding abstract argumentation frameworks (Baumann 2010) AF’ is an expansion of AF = ( A, C ) iff AF’ = ( A  A ’, C  C ’) for some nonempty A ’ disjoint from A such that: If (A,B)  C ’ then A  C ’ or B  C ’ Property: for any non-selfdefeating argument A there exist expansions in which A is justified But assumes that all arguments are attackable! 9

Resolution semantics (Modgil 2006; Baroni & Giacomin 2007) AF’ = ( A, C’ ) is a resolution of AF = ( A, C ) iff If (A,B)  C and (B,A) not in C then (A,B)  C’ If (A,B)  C and (B,A)  C then (A,B)  C’ or (B,A)  C’ If (A,B)  C’ then (A,B)  C A resolution is full if it leaves no symmetric attacks in C’ 10

Resolutions: some properties to be studied A B CD AF A B C D A B C D AF1 (A > B) AF2 (B > A) Grounded semantics satisfies Left to Right. Preferred semantics satisfies Right to Left X is justified in AF iff X is justified in all full resolutions of AF

Resolution semantics (Modgil 2006; Baroni & Giacomin 2007) AF’ = ( A, C ) is a resolution of AF = ( A, C ) iff If (A,B)  C and (B,A) not in C then (A,B)  C ’ If (A,B)  C and (B,A)  C then (A,B)  C ’ or (B,A)  C ’ If (A,B)  C ’ then (A,B)  C So assumes that: Only symmetric attacks can be resolved All attacks are independent from each other All symmetric attacks can be resolved 12

13 Resolution of asymmetric attack in ASPIC+ s1: r  ¬q K n =  ; K p = {q,r} r <’ q q qq r s1 > B1 A1 B2 B1 A1 B2

14 Resolution of asymmetric attack in ASPIC+ s1: r  ¬q s2: q  ¬r K n =  ; K p = {q,r} r <’ q q qq r s1 rr Constraint on  a : If A = B   then A ≈ a B > B1 A1 B2 A2 s2

15 John does not misbehave in the library John snores when nobody else is in the library John misbehaves in the library John snores in the library John may be removed R1: If you snore, you misbehave R2: If you snore when nobody else is around, you don’t misbehave R3: If you misbehave in the library, the librarian may remove you R1 < R2 R1 < R3, R2 < R3 R1R2 R3

16 John does not misbehave in the library John snores when nobody else is in the library John misbehaves in the library John snores in the library John may be removed R1: If you snore, you misbehave R2: If you snore when nobody else is around, you don’t misbehave R3: If you misbehave in the library, the librarian may remove you R1 < R2 R1 < R3, R2 < R3 R1R2 R3 R1 < R2

17 John does not misbehave in the library John snores when nobody else is in the library John misbehaves in the library John snores in the library John may be removed R1: If you snore, you misbehave R2: If you snore when nobody else is around, you don’t misbehave R3: If you misbehave in the library, the librarian may remove you R1 < R2 R1 < R3, R2 < R3 R1R2 R3 A1 A2 A3 B1 B2

18 R1: If you snore, you misbehave R2: If you snore when nobody else is around, you don’t misbehave R3: If you misbehave in the library, the librarian may remove you R1 < R2so A2 < B2 (with last link) R1 < R3, R2 < R3so B2 < A3 (with last link) A1 A2 A3 B1 B2

19 R1: If you snore, you misbehave R2: If you snore when nobody else is around, you don’t misbehave R3: If you misbehave in the library, the librarian may remove you R1 < R2so A2 < B2 (with last link) R1 < R3, R2 < R3so B2 < A3 (with last link) A1 A2 A3 B1 B2

20 John does not misbehave in the library John snores when nobody else is in the library John misbehaves in the library John Snores in the library John may be removed R1: If you snore, you misbehave R2: If you snore when nobody else is around, you don’t misbehave R3: If you misbehave in the library, the librarian may remove you R1 < R2 R1 < R3, R2 < R3 R1R2 R3

21 R1: If you snore, you misbehave R2: If you snore when nobody else is around, you don’t misbehave R3: If you misbehave in the library, the librarian may remove you R1 < R2so A2 < B2 (with last link) R1 < R3, R2 < R3so B2 < A3 (with last link) A1 A2 A3 B1 B2 Resolution semantics does not recognize that B2’s attacks on A2 and A3 are the same

22 R1: If you snore, you misbehave R2: If you snore when nobody else is around, you don’t misbehave R3: If you misbehave in the library, the librarian may remove you R1 < R2so A2 < B2 (with last link) R1 < R3, R2 < R3so B2 < A3 (with last link) A1 A2 A3 B1 B2 This is the correct outcome

Preference-based resolutions in ASPIC+ (Modgil & Prakken 2012) SAF’ = ( A, C, ≤’) preference-extends SAF = ( A, C, ≤) iff ≤  ≤ ’ X < Y implies X <’ Y Let D’ and D be the defeat relations of SAF’ and SAF. Then SAF’ is a resolution of SAF iff D’  D. Resolution SAF’ is a full resolution of SAF iff there exists no resolution SAF’’ of SAF such that D’’  D’ 23

Properties of preference-based resolutions Grounded semantics still satisfies LtoR sceptical (but only for finitary Afs) Preferred now fails RtoL sceptical

Counterexample to RtoL sceptical for preferred Counter-example to RtoL illustrates failure even when resolving only symmetric attacks Priority ordering over premises determines preferences over arguments Example (in Modgil & Prakken 2012) shows that no way to extend priority ordering (and hence preference ordering) exists so that D asymmetrically defeats B and E asymmetrically defeats C D E B C AX