A NEW FRAMEWORK FOR ABM BASED
ON ARGUMENTATIVE REASONING
SIMONE GABBRIELLINI AND PAOLOTORRONI
{SIMONE.GABBRIELLINI;PAOLO.T...
INTRODUCTION
• Argumentative approach to ABM
• Agents are socially embedded
• Agents exchange information by means
of simu...
FIRST STREAM
• Models of the first stream share at least
two common features:
• a network representation to mimic
social em...
SECOND STREAM
• The second stream focuses on
how social agents should reason
• These models rely on formal
logics and BDI ...
ARGUMENTATIVE AGENTS
• Our approach is grounded on well
established theories from social, cognitive,
and computer science....
EMBEDDED AGENTS
• The basic idea of embeddedness
comes from Granovetter’s hypothesis,
w h i c h s t a t e s t h a t o u r
...
EMBEDDED AGENTS
• We use a “caveman graph” to represent a
situation where clusters are maximally dense...
• We then allow ...
AGENT REASONING AND
INTERACTION
• According to Mercier & Sperber’s
argumentative theor y of reasoning,
reasoning developed...
AGENT REASONING AND
INTERACTION
• A d d r e s s e e f a c e s t w o
alternatives:
• either to reject the new
information (...
AGENT REASONING AND
INTERACTION
• Both addressee and source
may have to revise their own
opinions while involved in such
a...
ABSTRACT ARGUMENTATION
• An Argumentation Framework (AF)
is defined as a pair ⟨A,R⟩, where:
• A is a set of arguments
• R i...
ABSTRACT ARGUMENTATION
• D1: My government cannot
n e g o t i a t e w i t h y o u r
government because your
government doe...
SEMANTIC EXTENSIONS
• Abstract argumentation analyzes
AFs by means of semantics, i.e.
set of rules used to identify
“ c o ...
SIMULATED DIALOGUES
• A simulated dialogue D starts with an “invitation
to discuss” from A (source) to B (addressee), by
p...
AGAIN ON AGENT
REASONING
• As a framework, several points are left open:
• we do not commit to any specific
argumentation s...
ABM AND ARGUMENTS: NETARG
16
16giovedì 19 settembre 13
MODEL SCHEDULING
• At each time step, each agent A is asked
to start a dialogue with one of her
neighbors B, extracted at ...
OUTCOME MEASURE
• The opinion revision process gives
raise also to a polarization effect at
the population level
• Polariz...
EXPERIMENTAL RESULTS
19
19giovedì 19 settembre 13
EXPERIMENTAL RESULTS
20
20giovedì 19 settembre 13
EXPERIMENTAL RESULTS
21
21giovedì 19 settembre 13
CONCLUSIONS
• Using a network representation at different
levels (social embedding and information),
we have built a frame...
CONCLUSIONS
• Our framework explicitly models agents
reasoning capabilities and can be applied to
socially embedded and in...
THANKYOU FORYOUR
ATTENTION!!!
24
24giovedì 19 settembre 13
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A new framework for abm based on argumentative reasoning

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Using a network representation at different levels (social embedding and information), we have built a framework for social agents where reasoning is explicitly represented.
We used abstract argumentation and argumentative theory of reasoning to build agents that exchange information through simulated dialogues.
We demonstrated that our approach is, in principle, sufficient to reproduce two macro behaviors embedded in Granovetter’s theory, i.e., the tendency to inclusion of weak ties and a competitive advantage for non-isolated caves.
Our framework explicitly models agents reasoning capabilities and can be applied to socially embedded and interacting agents.
Our proposal:
- represents a way for qualitative approaches to fit ABM formal requirements;
- envisages possible new grounds for crossfertilization between computer sciences

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A new framework for abm based on argumentative reasoning

  1. 1. A NEW FRAMEWORK FOR ABM BASED ON ARGUMENTATIVE REASONING SIMONE GABBRIELLINI AND PAOLOTORRONI {SIMONE.GABBRIELLINI;PAOLO.TORRONI}@UNIBO.IT 1 1giovedì 19 settembre 13
  2. 2. INTRODUCTION • Argumentative approach to ABM • Agents are socially embedded • Agents exchange information by means of simulated dialogues. • We argue that this approach: • Allows a simple representation of actor’s reasoning, • helps filling the gap between scholars that represent explicitly agent’s reasoning and scholars that do not. 2 2giovedì 19 settembre 13
  3. 3. FIRST STREAM • Models of the first stream share at least two common features: • a network representation to mimic social embeddedness; • a preference for mathematical, game theoretical or evolutionary computing techniques. • It encompasses model of human hierarchies, trust and norm evolution, cooperation, cultural differentiation and collective behaviors, opinion dynamics and so on and so forth... 3 3giovedì 19 settembre 13
  4. 4. SECOND STREAM • The second stream focuses on how social agents should reason • These models rely on formal logics and BDI frameworks to represent agent opinions, tasks and decision-making capabilities. • It encompasses models of trust, cognitive representations and norms evolution and evaluation, and so on and so forth... 4 4giovedì 19 settembre 13
  5. 5. ARGUMENTATIVE AGENTS • Our approach is grounded on well established theories from social, cognitive, and computer science... • Many degrees of freedom: • Different embedding structures • Different trust models • Different ways of processing information • The only pivotal point is to represent information and reasoning with computational abstract argumentation. 5 5giovedì 19 settembre 13
  6. 6. EMBEDDED AGENTS • The basic idea of embeddedness comes from Granovetter’s hypothesis, w h i c h s t a t e s t h a t o u r acquaintances are less likely to be connected with each other than our close friends... • Granovetter called this type of bridges “weak ties”, and demonstrated their importance in permitting the flow of resources, particularly information, between otherwise unconnected clusters - i.e. small worlds... 6 6giovedì 19 settembre 13
  7. 7. EMBEDDED AGENTS • We use a “caveman graph” to represent a situation where clusters are maximally dense... • We then allow for two kind of structural settings: 1. each “cave” is disconnected from the others, thus agents can interact within their own cluster only; 2. a random number of bridges is added between caves, thus agents can interact occasionally with members of different caves. Even if our mechanism does not guarantee that all the caves become connected, on average the resulting networks exhibit small-world network characteristics... 7 1 2 7giovedì 19 settembre 13
  8. 8. AGENT REASONING AND INTERACTION • According to Mercier & Sperber’s argumentative theor y of reasoning, reasoning developed as a “tool” to convince others by means of arguments exchanged in dialogues • Let’s see a brief sketch of how it works: • Every time a bit of information is received, an addressee checks if the information is consistent with what she knows • If this is the case, the bit is included in addressee’s knowledge, otherwise, she has to react to avoid cognitive dissonance 8 8giovedì 19 settembre 13
  9. 9. AGENT REASONING AND INTERACTION • A d d r e s s e e f a c e s t w o alternatives: • either to reject the new information (addressee does not trust the source enough), and possibly rebut; • or to accept the new information (addressee trusts the source) and revise his/her own beliefs; 9 I claim x because y ??? 9giovedì 19 settembre 13
  10. 10. AGENT REASONING AND INTERACTION • Both addressee and source may have to revise their own opinions while involved in such a turn-taking interaction, until: • after revising, they both agree; • they decide to stop arguing because they do not trust each other... 10 10giovedì 19 settembre 13
  11. 11. ABSTRACT ARGUMENTATION • An Argumentation Framework (AF) is defined as a pair ⟨A,R⟩, where: • A is a set of arguments • R is a binary attacks relation over arguments, R ⊆ A×A, with α → β ∈ R interpreted as “argument α attacks argument β.” • In other words, an AF is a network of arguments, where directed links represent attack relations 11 11giovedì 19 settembre 13
  12. 12. ABSTRACT ARGUMENTATION • D1: My government cannot n e g o t i a t e w i t h y o u r government because your government doesn’t even recognize my government (a). • D2: Your government doesn’t recognize my government either (b). • D1: But your government is a terrorist government (c)... 12 a b c 12giovedì 19 settembre 13
  13. 13. SEMANTIC EXTENSIONS • Abstract argumentation analyzes AFs by means of semantics, i.e. set of rules used to identify “ c o h e r e n t ” s u b s e t s o f arguments. • Semantics may range from very credulous to very skeptical ones. • Each coherent set of arguments, according to the correspondent s e m a n t i c s , i s c a l l e d a n “extension” of A. 13 a b c 13giovedì 19 settembre 13
  14. 14. SIMULATED DIALOGUES • A simulated dialogue D starts with an “invitation to discuss” from A (source) to B (addressee), by picking a random argument β in her own extensions. • IF: B evaluates β as coherent with his own AF , dialog stops: they already “agree” • ELSE: if β is not included in any of B’s extensions, B faces an alternative: • if he trusts A, he will revise his own opinions by adding the new information and recalculating his semantic extensions • if he does not trust A, he either will quit the discussion or, if he can, rebut α→β and wait for A’s reaction • [So on and so forth until exit conditions...] 14 attack invitation 14giovedì 19 settembre 13
  15. 15. AGAIN ON AGENT REASONING • As a framework, several points are left open: • we do not commit to any specific argumentation semantics • we do not commit to any specific opinion revision mechanism. • We also assume that agents rely on a trust model.Arguably, a realistic model of trust would to take into account the authoritativeness, rank and social status of the interlocutor. • To date, our dialogue model is orthogonal to trust, we define trust thresholds statically but different trust models can be accommodated in the future. • Furthermore, in our model information is either accepted or rejected... 15 15giovedì 19 settembre 13
  16. 16. ABM AND ARGUMENTS: NETARG 16 16giovedì 19 settembre 13
  17. 17. MODEL SCHEDULING • At each time step, each agent A is asked to start a dialogue with one of her neighbors B, extracted at random, who could be restricted to the same cave or not, depending on the presence of bridges. • The probability to “argue” with members of the same cave is higher than with out- cave neighbors, according to the fact that bridges are less activated than strong ties. • A picks one random argument in her extensions and addresses B • B replies following the simulated dialogues procedure already sketched 17 17giovedì 19 settembre 13
  18. 18. OUTCOME MEASURE • The opinion revision process gives raise also to a polarization effect at the population level • Polarization occurs when the population divides into a small number of factions with high internal consensus and strong disagreement between them. • We measure the level of polarization Pt as the variance of the distribution of the AF distances dij,t, i.e. the AF distance between agents i and j at time t... 18 18giovedì 19 settembre 13
  19. 19. EXPERIMENTAL RESULTS 19 19giovedì 19 settembre 13
  20. 20. EXPERIMENTAL RESULTS 20 20giovedì 19 settembre 13
  21. 21. EXPERIMENTAL RESULTS 21 21giovedì 19 settembre 13
  22. 22. CONCLUSIONS • Using a network representation at different levels (social embedding and information), we have built a framework for social agents where reasoning is explicitly represented. • We used abstract argumentation and argumentative theory of reasoning to build agents that exchange information through simulated dialogues. • We demonstrated that our approach is, in principle, sufficient to reproduce two macro behaviors embedded in Granovetter’s theory, i.e., the tendency to inclusion of weak ties and a competitive advantage for non-isolated caves... 22 22giovedì 19 settembre 13
  23. 23. CONCLUSIONS • Our framework explicitly models agents reasoning capabilities and can be applied to socially embedded and interacting agents. • To the best of our knowledge, abstract argumentation has not been used for social simulation. • Our proposal: • represents a way for qualitative a p p r o a c h e s t o fi t A B M fo r m a l requirements... • envisages possible new grounds for cross- fertilization between the social and computer sciences... 23 23giovedì 19 settembre 13
  24. 24. THANKYOU FORYOUR ATTENTION!!! 24 24giovedì 19 settembre 13

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