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Automata Sel Berasaskan AgenAgent-Based Cellular Automata (ABCA) is a hybrid simulation framework that integrates the local transition rules of cellular automata with the autonomous behavioral logic of agent-Simulasi Kejadian Diskrit Berasaskan AgenAgent-based discrete-event simulation (AB-DES) is a hybrid modeling paradigm that couples autonomous agent behavior with an event-driven execution engine. It captures the decision-Model Markov Berasaskan AgenThe Agent-Based Markov Model (ABMM) is a hybrid simulation framework that embeds Markov chain state-transition logic inside individual autonomous agents. Each agent independently sSimulasi Mikro Berasaskan AgenAgent-based microsimulation (ABMS) merges traditional microsimulation's individual-level statistical tracking with agent-based modeling's behavioral rules and interaction mechanismPemodelan Berasaskan Agen (ABM)Agent-based modeling (ABM) is a computational simulation method, formalized through the work of Thomas Schelling and Robert Axelrod in the 1970s–1990s, that simulates the behavior Optimisasi Berbilang Objektif Berasaskan AgenAgent-based multi-objective optimization (ABMOO) embeds autonomous agents inside a simulation environment and evolves their behavior or parameters to simultaneously optimize two or

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Kaedah asas yang paling banyak dirujuk bagi topik ini, mengikut susunan ia dibangunkan — tempat untuk bermula jika anda baharu di sini.

  1. Pengoptimuman Pelbagai Objektif1896 (concept); 1989–2002 (evolutionary algorithms era)oleh Vilfredo Pareto (concept); modern computational formulation by Goldberg and Deb et al.
  2. Model Markov1906oleh Andrei Markov
  3. Markov Chain Monte Carlo (MCMC)1953 (Metropolis-Hastings); 1984 (Gibbs)oleh Metropolis et al. (1953); Gibbs sampler formalised by Geman & Geman (1984)
  4. Simulasi Kejadian Diskrit (DES)1960s (formalized); modern computational form from 1970s onwardoleh Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s)
  5. System Dynamics1961oleh Jay W. Forrester
  6. Analisis Skenario Polisi1967–1990soleh Kahn, H. & Wiener, A. J. (seminal); adapted for policy by RAND Corporation and OECD
  7. Pemodelan Berasaskan Agen (ABM)1970s–1990s (formalized as a field)oleh Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)
  8. Pensampelan Hiperkubus Latin1979
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Automata Sel Berasaskan AgenSimulasi Kejadian Diskrit Berasaskan AgenModel Markov Berasaskan AgenSimulasi Mikro Berasaskan AgenPemodelan Berasaskan Agen (ABM)Optimisasi Berbilang Objektif Berasaskan AgenAnalisis Senario Berasaskan AgenAnalisis Sensitiviti Berasaskan AgenSistem Dinamik Berasaskan AgenAutomata SelularPemodelan Berasaskan Agen DeterministikAutomata Sel DeterministikSimulasi Kejadian Diskrit DeterministikModel Markov BerketentuanSimulasi Mikro DeterministikOptimisasi Multi-Objektif DeterministikAnalisis Senario DeterministikAnalisis Sensitiviti DeterministikDinamika Sistem DeterministikSimulasi Digital TwinSimulasi Pilihan DiskritSimulasi Kejadian Diskrit (DES)Simulasi Sistem Kejadian DiskritPenapis Kalman EnsembelAnalisis FraktalSimulasi Geant4Analisis Sensitiviti GlobalImportance SamplingModel Ising Monte CarloPensampelan Hiperkubus LatinKaedah Longstaff-SchwartzMarkov Chain Monte Carlo (MCMC)Model MarkovModel Simulasi MikroPengangkutan Neutron & Zarah Monte CarloProses Variasi Monte CarloPemodelan Berasaskan Agen Berbilang ObjektifMulti-Objective Cellular AutomataSimulasi Peristiwa Diskret Multi-ObjektifModel Markov Objektif PelbagaiMulti-objective microsimulationPengoptimuman Pelbagai ObjektifAnalisis Skenario Multi-objektifAnalisis Sensitiviti Pelbagai ObjektifDinamika Sistem Pelbagai ObjektifPath Integral Monte CarloPemodelan Berasaskan Ejen Skenario DasarAnalisis Skenario PolisiPolicy Scenario Cellular AutomataSimulasi Kejadian Diskrit Skenario Dasar KebijakanSimulasi Mikro Skenario PolisiSimulasi Monte Carlo Senario DasarOptimasi Pelbagai Objektif Skenario DasarAnalisis Sensitiviti Skenario Dasar KebijakanSistem Dinamik Skenario Dasar Dasar KebijakanKuantum Monte CarloAnalisis Kuantifikasi Kecerunan Semula (RQA)Pemodelan Berasaskan Agen TeguhSimulasi Peristiwa Diskrit TeguhModel Markov TeguhSimulasi Mikro MantapPengoptimuman Pelbagai Objektif yang TeguhAnalisis Senario TeguhAnalisis Sensitiviti MantapSample EntropyAnalisis Senario dan Simulasi 'Bagaimana Jika'Gelongsoran Kendiri TeraturPenyelidikan Pengesahan Dibantu SimulasiCarta Kawalan Dibantu SimulasiAnalisis Pohon Peristiwa Berbantuan SimulasiAnalisis Mod Kegagalan dan Kesan Bantuan SimulasiAnalisis Pohon Kegagalan Dibantu SimulasiUjian Hipotesis Dibantu SimulasiAnalisis Kapabiliti Proses Bantuan SimulasiAnalisis Kandungan Kuantitatif Dibantu SimulasiAnalisis Kebolehpercayaan Bantuan SimulasiKawalan Proses Statistik Berbantukan SimulasiPenyelidikan Trend Berbantukan SimulasiAutomata Sel StokastikPersamaan Pembezaan Stokastik (SDEs)Simulasi Kejadian Diskrit StokastikModel Markov StokastikMikrosimulasi StokastikPengoptimuman Pelbagai Objektif StokastikAnalisis Skenario StokastikAnalisis Sensitiviti StokastikDinamik Sistem StokastikSystem DynamicsValue at Risk (VaR)Teknik Pengurangan Varians untuk Simulasi Monte CarloVEGAS Monte Carlo