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Simulació / Simulation

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01General#

method purpose mathematical foundation description level # levels attributes time state change communication between agents complexity of agents # agents applications cons software
Systems dynamics and world prediction differential equations
  • describes the target system as a single entity or object: a system dynamics model is an indivisible whole
 macro 1 continuous approximating continuous time deterministic no low 1
  • hawks, doves, law-abiders
  • world models
Microanalytical (MSM) prediction Markov chains
  • aggregate level +
    lower level[s]
  • methodologies
    • static
    • dynamic
    • longitudinal
  • use representative available detailed information about the initial state of microunits
 micro 2 discrete discrete, equidistant stochastic no high many
  • tax revenue
  • demography
  • extremely data-based
  • very demanding (computing, storage)
Queuing
  • servers +
    queues +
    customers
    (+ agenda)
  • discrete event models
  • sthocastic
 1 no low many
  • bank
  • computer resources (cpu, printer...)
  • airport
  • public administration
Multilevel explanation
  • sthocastic processes
  • synergetics
  • synergetics
 multi 2+ continuous, discrete continuous, discrete deterministic, sthocastic maybe low many
  • opinion formation
  • gender segregation
  • law-abider (rev.)
Cellular automata
  • cells in a regular grid
  • few states for each cell
  • state changes at each time step
  • state = F(previous state, neighbourhood cells)
  • local interactions
 2 yes low many
  • the game of life
  • gossip
  • majority
  • Axelrod's tribute
  • migration
  • Game of Life
  • (LISP implementations)
Multi-agents (distributed AI) explanation - (rules)
  • agents properties
    • autonomy
    • social ability
    • reactivity
    • proactivity
  • problems
    • fragility
    • complexity
    • lack of common sense
  • solutions
    • production systems
    • object orientation
    • language parsing and generation
    • machine learning
 multi 2+ discrete discrete, event driven rules yes high few
  • Sugarscape
  • MANTA (ants)
  • Evolution of Organised Society (EOS)
Learning and evolutionary
  • neural networks
  • genetic algorithms
    • crossover
    • mutation
  • evolution strategies, evolutionary programming
 2+ maybe high many
  • neural networks
    • learning a lexicon
    • learning to be altruistic
  • genetic algorithms
    • prisoner's dilemma
Note:

Programari / Software

02Llibres / Books#

03Economia / Economics#

04Publicacions / Publications#

05Recerca / Research#

http://www.francescpinyol.cat/simulacio.html
Primera versió / First version: 22.I.2002
Darrera modificació: 3 d'octubre de 2002 / Last update: 3rd October 2002

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