Tabela de conteúdos

Agent-based modelling with TerraME

P. R. Andrade, T.O. Assis, T.G.S. Carneiro, A.M.V. Moneiro, G. Camara, A.P.D. Aguiar

Procurar por comparison of agent-based modeling software no wikipedia. Possuem alguma integracao com SIG: AnyLogic, Cormas, Framesticks, MASON, RePast, SeSAM, NetLogo, VisualBoots.

Replication

Referencias do JASSS a serem lidas

A Survey of Agent-Based Modeling Practices (January 1998 to July 2008)

Brian Heath, Raymond Hill and Frank Ciarallo12(4):9 html

Design Guidelines for Agent Based Model Visualization

Daniel Kornhauser, Uri Wilensky and William Rand12(2):1 html

Tools of the Trade: A Survey of Various Agent Based Modeling Platforms

Cynthia Nikolai and Gregory Madey12(2):2 html

REsCape: an Agent-Based Framework for Modeling Resources, Ethnicity, and Conflict

Ravi Bhavnani, Dan Miodownik and Jonas Nart11(2):7html

Communication Between Process and Structure: Modelling and Simulating Message Reference Networks with COM/TE

Thomas Malsch, Christoph Schlieder, Peter Kiefer, Maren Lübcke, Rasco Perschke, Marco Schmitt and Klaus Stein10(1):9html

Individual-Based Modelling and Ecology

Grimm, Volker and Railsback, Steven F.Reviewed by Marco A. Janssen9(4)html

The Spatial Dimension and Social Simulations: A Review of Three Books

Reviewed by Riccardo Boero9(4)html

An Agent-Based Spatially Explicit Epidemiological Model in MASON

Jill Bigley Dunham9(1):3html

MAS-SOC: a Social Simulation Platform Based on Agent-Oriented Programming

Rafael H Bordini, Antônio Carlos da Rocha Costa, Jomi F. Hübner, Fabio Yoshimitsu Okuyama, Álvaro F. Moreira and Renata Vieira8(3):7html

Technical Note: Evaluating Java Development Kits for Agent-Based Modeling

Nils B. Weidmann and Luc Girardin8(2):8html

Case-Based Reasoning, Social Dilemmas, and a New Equilibrium Concept

Luis R. Izquierdo, Nicholas M. Gotts and J. Gary Polhill7(3):1html

Modelos a serem implementados

The Evolution of Altruism in Spatially Structured Populations

András Németh and Károly Takács (2007)html

Abstract: […] Here we examine the evolution of […] altruism with a focus on altruistic teaching. Teaching is modeled as a knowledge transfer which enhances the survival chances of the recipient, but reduces the reproductive efficiency of the provider. […]

for (every living_agent x):
  if (random(1000) < innovation_rate) x.knowledge:=1;
  if ((x.teacher) && (x.knowledge=1)):
    repeat // search for an agent without knowledge
      if (proximity_based) y := random_agent_in_proximity
      else y := random_agent;
    until (y.knowledge = 0)
  if (y.learning)
    y.knowledge := 1;
    x.breeading_chance := x.breeading_chance - costs;
  end if
end for

Group Reputation Supports Beneficent Norms

David Hales (2002)html

Abstract: This paper demonstrates the role of group normative reputation in the promotion of an aggression reducing possession norm in an artificial society. […]

LOOP 50 times
  Select an agent (A) at random from the population (with replacement)
  Activate agent - (agent (A) selects and executes one action):
   IF appropriate - receive reputational information from all neighbours
   IF current cell contains food then
      IF food prepared then {EAT-FOOD}
      IF food picked-up then {PREPARE-FOOD}
      IF food not-picked-up then {PICKUP-FOOD}
   END IF
   IF free food item is visible in neighbourhood {MOVE} to food item.
   IF a food item can be smelled two cells away then {MOVE} towards it.
   IF an agent holds a food item one cell away in neighbourhood then
     IF current strategy allows then {ATTACK}
   END IF
   IF any neighbouring cells are free then select one at random and {MOVE}
   No other actions are possible so {PAUSE}
END LOOP

Identifying cases of social contagion using memetic isolation: comparison of the dynamics of a multisociety simulation with an ethnographic data set

Derek Gatherer (2002)html

Abstract: A simulation is presented of a grid of connected societies of reproducing agents. These agents are capable of horizontal and vertical transmission of non-genetic cultural traits (memes). […]

INITIALIZATION:
  For each of the 100 cells in the 10-by-10 array:
  {
    place two Agents in each cell
    randomly assign one of four Gene attributes to each individual
    randomly assign one of four Meme attributes to each individual
  }
ITERATION:
  For 100 generations do the following:
  {
    For each Agent:
    {
      If Agent Meme attribute = "A" and CultSel = "Y"
      {
        Double parameters n and o for that agent
      }
      If Agent Meme attribute = "A" and NatSel = "Y"
      {
        Double parameter r for that agent
      }
      If a random number x < r
      {
        Reproduce Agent
      }
      If a different random number y < o
      {
        If same random number y is also < n
        {
          Transmit Meme to any Agent in any adjacent cell
        }
        else
        {
          Transmit Meme to any Agent in same cell
        }
      }
      If a different random number z < m
      {
        Migrate Agent to adjacent cell
      }
    }
  }
END.