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A Dialogical Logic-based Simulation Architecturefor Social Agents
and the Emergence of Extremist Behaviour
Piter Dykstra1,2, Corinna Elsenbroich3, Wander Jager1,Gerard Renardel de Lavalette1, Rineke Verbrugge1
1Groningen University,Groningen ,The Netherlands
2Hanzehogeschool Groningen,Groningen ,The Netherlands
3University of Surrey,Guildford, United Kingdom
September 10, 2009
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
1 Introduction
2 Groups & Extreme OpinionsThe ”Henhouse”-modelThe Demo
3 ArgumentationDialogical LogicModel with Dialogues
4 Concluding Remarks
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
Central Question
What causes the emergence of extreme opinions?
Goal
Agent-based Simulation with Reasoning Agents
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
Central Question
What causes the emergence of extreme opinions?
Goal
Agent-based Simulation with Reasoning Agents
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
The ”Henhouse”-model
Actions
Announcements
LoudnessEvidenceImportance
Adopt opinion from other agents (assimilation)
Move elsewhere (segregation)
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
The ”Henhouse”-model
The Topic Space
Simulation of Common Knowledge
Accumulation of evidence and importanceForgetting
Formation of groups of agents
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
The ”Henhouse”-model
The Topic Space
Simulation of Common Knowledge
Accumulation of evidence and importanceForgetting
Formation of groups of agents
Reputation Status is determined by similarity with environment.Goal: Maximize RS
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
The Demo
RationalAgent program in an initial state
(A) (B) (C)Agents Evidence Importance
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
The Demo
RationalAgent with social knowledge
(A) (B) (C)Agents Evidence Importance
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
The Demo
Results I
Emergence of extreme opinions
Decrease of importance of opinions(and communication)
Formation of (different kinds of) groups.
No reasoning or argumentation involved
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
Dialogical Logic
Dialogues in Rational Agents
Proponent - Opponent
Initial AnnouncementAttacksDefences
Alternating Moves
WinningPay - Reward
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
Dialogical Logic
Dialogues
Proponent - Opponent
Initial AnnouncementAttacksDefences
Alternating Moves
WinningPay - Reward
Reputation Status is determined by winning and losing dialogues.
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
Dialogical Logic
Example of a Dialogue
A: If we do not have enough funding and refugees createadditional costs, then they should leave this country.
B: Why do you say that?
A: Well, prove me wrong! If you can I give you 1RS but if I amright you have to pay me 0.50RS .
B: Ok, deal. I really disagree with your conclusion. . . .
A: Do you agree then that we do not have enough funding andthat refugees create additional costs.
B: Yes of course, that can hardly be denied.
A: Right. . . – people, do you believe refugees should leave thiscountry?
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
Dialogical Logic
2-D Logic
Evidence:
E (ϕ) = P(ϕ)P(ϕ)+R(ϕ)
Importance:
I (ϕ) = P(ϕ)+R(ϕ)2
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
Dialogical Logic
2-D Logic
Evidence:
E (ϕ) = P(ϕ)P(ϕ)+R(ϕ)
Importance:
I (ϕ) = P(ϕ)+R(ϕ)2
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
Model with Dialogues
RationalAgent with dialogues
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
Model with Dialogues
Results II
No extremization of opinions
No decrease of importance
One agent wins all the RS-pointsand determines the ruling opinion
Communication stops
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
Logic in Rational Agents
Epistemic Logic for Higher Order Reasoning
Pitfall: the perfect reasoner
Dialogical
Non-Monotonic
Multi-Valued
Paraconsistent
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture
Introduction Groups & Extreme Opinions Argumentation Concluding Remarks
The Competition
Social Network Analysis (Sun and Breiger)
Belief-Desire-Intention (Flache & Macy)
Game Theory (van Benthem)
Constructuralism (Carley)
Piter Dykstra et al. A Dialogical Logic-based Simulation Architecture