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Agent-based modeling of social conflict, civil violence and revolution: state-of-the-art review and further prospects Carlos Lemos 1,2,3, Helder Coelho.

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Presentation on theme: "Agent-based modeling of social conflict, civil violence and revolution: state-of-the-art review and further prospects Carlos Lemos 1,2,3, Helder Coelho."— Presentation transcript:

1 Agent-based modeling of social conflict, civil violence and revolution: state-of-the-art review and further prospects Carlos Lemos 1,2,3, Helder Coelho 2, Rui J. Lopes 3,4 1 Instituto de Estudos Superiores Militares (IESM), Lisbon, Portugal 2 Faculty of Sciences of the University of Lisbon, Portugal 3 Instituto Universitário de Lisboa (ISCTE-IUL), Lisbon, Portugal 4 Instituto de Telecomunicações IT-IUL, Lisbon, Portugal 1 EUMAS2013 – Toulouse 12/14 December 2013

2 http://www.bing.com/images/search?q=manifesta%c 3%a7%c3%a3o+15+setembro+parlamento+mulher+n ua&view=detail&id=5D88C21BFC553882E91EC717DD A46BD213F08FBA 2 http://1.bp.blogspot.com/-v0yD5CrO8Fw/UFb4b8BmT3I/AAAAAAAAV6s/Djq5mzkqM4M/s1600/222222.jpg http://db2.stb.s-msn.com/i/7B/F35CB26D513744D8A788DD7E24A8B.jpg http://www.meiosepublicidade.pt/wp-content/uploads/2012/11/carga-policial-300x222.jpg CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK) EUMAS2013 – Toulouse 12/14 December 2013

3 3 QUESTIONS: How do large protest demonstrations form and how can these turn to violent confrontation? How do protest demonstrations change the social and political context? Can these links be understood? Predicted? Controlled? EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK)

4 4 SOCIAL CONFLICT PHENOMENA: tentative classification framework Peaceful protest demonstrations, flash mobs Protest demonstrations, with violence Riots Insurgence, terrorism Civil War, International War EMERGENCE, CAS behavior TRANSITIONS Intensity Psychology, Sociology, History Security Studies, Police Studies Military Sciences (Military History, Military Strategy, Operational Art) Hierarchical Thinking & Approaches EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK) Portugal Greece Brazil Egypt Afghanistan Syria

5 5 Protest C OUNTRY SOCIAL CONTEXT Political, Economic, Social: #protests, violence … … … … W ORLD media, SN … COMPLEXPATH DEPENDENT EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK) INTENSITY Time

6 ABM OF SOCIAL CONFLICT, CIVIL VIOLENCE AND REVOLUTION: Framework – simplified ODD (Grimm et al., 2010) 6 DESCRIPTION Purpose Scope of the model (type of phenomena to be simulated) Entities Agent types (attributes, rules, environment) Basic time cycle Time cycle, sequence, synch./asynch. activation Model results Scales, phenomena explained Observation Use of empirical parametrization/validation Model strengths & limitations Explanatory power, gaps between model results and reality EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK)

7 REVIEW: Seven models Civil violence Worker protest Riots Urban crime Revolution Guerrilla warfare 7 EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK)

8 EPSTEIN (2002): Modeling civil violence: An Agent-Based computational approach Purpose: simulation of rebellion against a central authority or violence between 2 groups population quiet rebellious jailed move at random police move at random arrest rebellious agents within vision radius perceived grievance G =H×(1-L) net risk N=R×P×J α 8 Source: Epstein (2002) safe havens in peacekeeping outbursts of violencegradual reduction of police EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK)

9 9 (VERY) PRELIMINARY RESULTS: all quiet before a burst of rebellion… EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK)

10 10 (VERY) PRELIMINARY RESULTS: … and now a large rebellious uprise ! EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK)

11 11 collective behavior memory/memoryless reactive/deliberative events environmental features grievance net risk perception threshold RATIONAL BEHAVIOR MODEL RULE-BASED BEHAVIOR MODEL CHANGE STATE, SELECT/PERFORM ACTION FINDINGS: agent behavior frameworks in S-O-A models EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK)

12 12 FINDINGS: strengths & explanatory power of ABM Intermittent bursts of rebellion/violence (punctuated equilibrium) [Epsteins model and derived ABM] Deceptive behavior in protester/police interaction [Idem] Instability of authoritarian regimes if access to ICT is sufficiently widespread (cascade of reference revelation leading to revolution) [Makowsky & Rubin model] Multi-step concept + empirical validation soundness + robustness + realism [Davies et al. model; Fonoberova et al. model] EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK)

13 13 FINDINGS: gaps between ABM and reality Need to relate grievance G, hardship H, etc. to Relative Deprivation (RD) [Social psychology, empirical data] Assembling stage not treated as a contagion process with multiple contexts [Network theory, empirical data] Effect of formal/informal media coverage not considered [New types of agentes (e.g. media, agitators)] Modeling of police tactics (mostly …) missing [Refining police agent models] Path dependence due to successive events not considered [Multiple 2-step cycles] EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK)

14 14 FUTURE TRENDS & ONGOING WORK Aim for a framework with two-step cycles (CONTAGION PROTEST) (CONTAGION PROTEST) … Assembling/contagion model with multiple contexts Complex contagion + layered NW Protest model Start with Epsteins model, refine agent types/attibutes/behavior, add new types of agents Parametrization/validation Collect & process data in real events (images, videos, questionnaires) Obtain data on news sites, activist group sites, etc. EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK)

15 nodes may not be connected in individual context (source: Hamill, 2006) 15 FUTURE TRENDS & ONGOING WORK: the layered network concept concept (source: Hamill, 2006) criteria for tie strength (source: Hamill, 2006)... … but are linked in multiple influence contexts (source: Hamill, 2006) EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK)

16 16 (VERY) PRELIMINARY RESULTS: analysis of Facebook network of Que se Lixe a Troika – Queremos as nossas vidas political activist group friendship network: giant component, community structures, filtering by node degree group interactions network: hubs of activity EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK)

17 17 (VERY) PRELIMINARY RESULTS: grievance factors, from questionnaires EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK)

18 18 QUESTIONS ? EUMAS2013 – Toulouse 12/14 December 2013

19 FUTURE TRENDS & ONGOING WORK: contagion models Dodds and Watts (2005) SIR network contagion model (Complex contagion, memory effects) * Watts and Dodds (2007) 2-step model of influence (Complex contagion, memoryless, rule-based) Individual decision: keep A or adopt B * Berry et al. (2004) Group recruitment model 19 EUMAS2013 – Toulouse 12/14 December 2013 CONTEXT & MOTIVATIONCONFLICT & PROTEST DYNAMICSSOA REVIEWDISCUSSIONFUTURE PROSPECTS (ONGOING WORK)

20 20 EUMAS2013 – Toulouse 12/14 December 2013 Purpose: describe recruitment of urban street gangs (surrogate of terrorist groups) Agents: simple agents (2 attributes+School Attendance Tendency – SAT, connected by social networks) + abstract agents (School and Gang) Assumptions: simple agents (teenagers) decide to attend school or joint gang depending on where G index is cumulative (inflence of past association with gang) and T is a threshold Source: Berry et al. (2004) Berry et al. (2004): Computational Social Dynamic Modeling of Group Recruitment, Sandia National Laboratory Report SAND2003-8754

21 21 EUMAS2013 – Toulouse 12/14 December 2013 Makowsky & Rubin (2011): An Agent-Based Model of Centralized Institutions, Social Network Technology, and Revolutions, Working Paper 2011-05, Towson University Purpose: study large scale social change in authoritarian regimes and influence of ICT (e.g. Arab Spring Revolution) Agents: citizens, central authority (government), non-central authority (e.g. police) Assumptions: citizens hide/show preference against authority by maximizing an utility function: central authority may change preference (institutional change) and non-central authority may support central authority or citizens, by maximizing their utility functions:

22 22 EUMAS2013 – Toulouse 12/14 December 2013 REPRESENTATIVE RESULTS (source: Makowsky & Rubin, 2011):

23 23 EUMAS2013 – Toulouse 12/14 December 2013 Assessment of Makowsly & Rubin (2011) model: ADVANTAGES: Explains revolution as a contagion process of cascade preference revelation Can represent sublevation of non-central authority Can represent institutional revolution (social context) changes due to revolution (closes loop) LIMITATIONS: Agents (citizens, n.c. authority) cannot move Agent actions in protests not represented (essentially a contagion model) Unrealistic modeling of SN/ICT (oversimplification of SN topology) Modeling of agents behavior not as effective as Epsteins

24 24 EUMAS2013 – Toulouse 12/14 December 2013 A. Ilachinsky (2004): EINStein combat model (in Artificial War. Multi-Agent-Based Simulation of Combat, World Scientific) Purpose: AB model of land combat Agents: Agent hierarchy (fireman, squad commander, force commander, supreme commander), multiple squads, realistic terrain features, and personality and goal-driven combat/movement actions Formulation: agents select action (move/combat) by minimizing a penalty function: Source: Ilachinsky (2004) personality vector

25 25 EUMAS2013 – Toulouse 12/14 December 2013 Assessment of Ilachinsky (2004) model: ADVANTAGES: Useful framework for modeling police forces (actions, movement and hierarchical structure) More realistic agent behavior Rich collective/emergent behavior patterns Realistic scenarios (not considered in simpler models) Can still deal with a significant number of agents LIMITATIONS: Substantially more complicated than e.g. Epsteins model and related variants More demanding in terms of computer resources Maximization/minimization less efficient than threshold comparison Requires substantial reworking for agents other than police forces (?)

26 26 EUMAS2013 – Toulouse 12/14 December 2013 Assessment of Ilachinsky (2004) model: ADVANTAGES: Useful framework for modeling police forces (actions, movement and hierarchical structure) More realistic agent behavior Rich collective/emergent behavior patterns Realistic scenarios (not considered in simpler models) Can still deal with a significant number of agents LIMITATIONS: Substantially more complicated than e.g. Epsteins model and related variants More demanding in terms of computer resources Maximization/minimization less efficient than threshold comparison Requires substantial reworking for agents other than police forces (?)

27 27 EUMAS2013 – Toulouse 12/14 December 2013 F. Durupɩnar(2010): From Audiences to Mobs: Crowd Simulation with Psychological Factors, PhD Thesis (continuation) 5 factor model of personality: Openness, Consciousness, Extroversion, Aggreableness, Neuroticism Emotion model: Ortony, Clore and Collins (OCC) 22 emotion-model * temperament; average emotional state; less permanent than personality but more persistent than emotions Source: Durupɩnar (2004)


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