ABM for Systems Biology

AGENT-BASED MODELLING FOR SYSTEMS BIOLOGY

Software for developing Agent-Based Models

Software for developing Agent-Based Models

There are many different libraries and toolkits for implementing agent-based models. Most of them use an object-oriented programming language such as Java or Objective-C.

To find software that supports particular requirements, tick the boxes that apply:

	Statically defined groups. These can be used to define non-spatial neighbourhoods e.g. signalling networks across distances.
	Organisational metaphors for dynamic groups. Agents can enter and leave groups at different times based on defined conditions.
	Situated agents. Agents can be modelled as being located in a spatial environment and the space is explicitly modelled.
	Agents in motion.
	Local variables with their own evolution rules. Variables can be spatially sensitive and state transitions can be spatially defined.
	Global variables with their own evolution rules. Variables in the "background" can evolve according to their own set of rules.
	Reactive agents. Agents' behaviuoral rules can be based on the state of their environment.
	Proactive agents. Agents' behavioural rules can be determined by their own internal states, data representations, propensities etc..
	Adaptive agents. Agents can obey different rules or the rules can themselves evolve through time.

The Swarm Wiki page at: http://www.swarm.org/wiki/Main_Page has reviews of agent-based modelling software and links to software.