text: In particle-based (sometimes called "agent-based") simulations, proteins, nucleic acids, macromolecular complexes or small molecules are represented as individual software objects, and their progress is tracked through the course of the entire simulation. Because particle-based rule evaluation keeps track of individual particles rather than populations, it comes at a higher computational cost when modeling systems with a high total number of particles, but a small number of kinds (or pools) of particles. In cases of combinatorial complexity, however, the modeling of individual particles is an advantage because, at any given point in the simulation, only existing molecules, their states and the reactions they can undergo need to be considered. Particle-based rule evaluation does not require the generation of complete or partial reaction networks at the start of the simulation or at any other point in the simulation and is therefore called "network-free".
  This method reduces the complexity of the model at the simulation stage, and thereby saves time and computational power. The simulation follows each particle, and at each simulation step, a particle only "sees" the reactions (or rules) that apply to it. This depends on the state of the particle and, in some implementation, on the states of its neighbours in a holoenzyme or complex. As the simulation proceeds, the states of particles are updated according to the rules that are fired.
  Some particle-based simulation packages use an ad-hoc formalism for specification of reactants, parameters and rules. Others can read files in a recognised rule-based specification format such as BNGL.