विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| एजेंट-आधारित मार्कोव मॉडल× | विच्छिन्न-घटना अनुकरण (Discrete-Event Simulation - DES)× | |
|---|---|---|
| क्षेत्र | अनुकरण | अनुकरण |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | 2000s | 1960s (formalized); modern computational form from 1970s onward |
| प्रवर्तक≠ | Hybrid approach synthesized from Bonabeau (ABM) and Norris/classical Markov chain literature | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) |
| प्रकार≠ | Hybrid simulation — agent-based modeling with Markov state transitions | Stochastic process simulation |
| मौलिक स्रोत≠ | Bonabeau, E. (2002). Agent-based modeling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences, 99(Suppl 3), 7280-7287. DOI ↗ | Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127 |
| उपनाम≠ | ABMM, Agent-Based Markov Chain Model, ABM-Markov hybrid, Agent Markov simulation | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) |
| संबंधित≠ | 5 | 4 |
| सारांश≠ | The Agent-Based Markov Model (ABMM) is a hybrid simulation framework that embeds Markov chain state-transition logic inside individual autonomous agents. Each agent independently samples its next state from a probability transition matrix, enabling the model to capture both micro-level heterogeneity across agents and the tractable probabilistic structure of Markov chains. The approach is widely used in health economics, epidemiology, social science, and operations research. | Discrete-Event Simulation (DES) is a computational modeling paradigm in which the state of a system changes only at a countable sequence of points in time — the events. Between events nothing changes, so the simulation clock jumps directly from one event to the next. Formalized through the foundational textbooks of Banks, Carson, Nelson and Nicol and of Law in the 1960s–2000s, DES has become the standard tool for analyzing queuing systems, healthcare patient flows, manufacturing lines, and logistics networks where entities move through resources over time. |
| ScholarGateडेटासेट ↗ |
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