From, MIT Press: when a system is capable of reprogramming itself in response to outside signals, it can be modeled as an adaptive agent.
- Agents are enclosed within a boundary.
- Agents filter outside signals through boundaries.
- Agents are . They may accept some signals and ignore others (if/else). Signals may be recursive (feedback loops). Boundaries are places where a feedback loop can be halted. They provide a "breakpoint" in the loop.
- Within the boundary, agents carry histories, or "state" — the result of their individual reactions to signals over time.
- Multiple agents can form conglomerates — higher levels of organization. Conglomerates can also be seen as agents.
- Agents reprogram themselves in response to outside signals - this means both adapting behavior to signals (if/else), and changing the structure of the "programs" that generate the behavior in the first place.
In machine learning, evolution is often provided by a that produces a reward for agents that move closer toward some desired goal.for
In a evolution:, this doesn't cut it. The behavior of a CAS is too complex to be easily expressed as a fitness function. In a real sense, complex adaptive systems don't have a singular "goal". They are . To model these systems in a way that will produce realistic
- Agents are situated within a landscape. This landscape contains resources (e.g. food). Resources are heterogenous and distributed unevenly.
- Agents reproduce by collecting resources.
A challenge for modeling generative grammar that can produce both the signals and the boundaries of the system.: finding a
Theexpresses computer programs as networks of adaptive agents.
is often used to derive models for aspects of complex adaptive sytems.
Most can agents turn out be persistent patterns imposed on flows. As was mentioned earlier, the human body turns over most resident atoms within days, and no atom resides in the body for more than a year or so. Similarly, in a great city, individuals arrive and depart daily but the overall pattern of activity persists.
— John Holland,