A cyberorganism may freely split and join
other organisms, its parts may be distributed, and
the parts may be destroyed and regenerate.

inherently parallel actor languages that enable the use of multicore processors. However, to facilitate more complex and interesting services, software must be able to endure and adapt. Thus, the concept of an actor as an ephemeral process tied to a single computer at a time is not sufficient to execute such services.

Endurance and adaptation are common traits in natural systems that require a relatively “long” life cycle depending on their ability to adapt through feedback mechanisms provided by the environment. Natural selection uses such feedback to change the programming of organisms.

Organisms with mobility and more complex functions (like animals in nature) use environmental feedback to learn complex new tasks. Software must also learn to purposefully navigate its environment. As such, it must be more like an animal: mobile and able to forage for resources, learn from the environment, evolve, and provide services. One can imagine cyberorganisms [ 2] roaming the pervasive cyberspace, gaining “wealth” by providing services, negotiating with computers to sense the environment, and computing, actuating, and learning (self-modifying) from the results of their actions.

This is not to argue that software will be entirely analogous to biological hardware—even if we were to create biological computers, as we will eventually. An innatedifference between organisms and software will persist: Software cannot directly sense, compute, or affect its environment; rather, it depends on the availability of computer nodes and networks. It is like a Platonic ideal of mind with a life independent of a physical body, albeit one that may move from one body to another, adapt itself or modify how the body it controls may operate.

However, this metaphor also suggests the possibility of a different sort of resilience: a cyberorganism need not be bounded in space and time like its biological counterparts. Rather, it may freely split and join other organisms, its parts may be distributed, and the parts may be destroyed and possibly regenerate.

In pervasive cyberspace, no central authority exercises complete control over the actions of cyberorganisms. This does not mean that control mechanisms will be entirely absent. We can foresee a pervasive cyberspace with many autonomous monitoring agents and mechanisms that limit access. Some mechanisms will affect systems as a whole, others the interaction among nominally independent systems. Some of these monitoring-and-control mechanisms will affect macro-level properties of systems, much as a central bank influences the emergent properties of a national economy by controlling key interest rates.

We are at the threshold of an entirely new science of computing, one that will be inspired by the biological metaphor, not by the notion of algorithm. Reporting this scientific evolution, the next 50 years of CACM should make even more exciting reading than the previous 50 years. ^c

REFERENCES

1. Agha, G. Concurrent object-oriented programming. Commun. ACM 33, 9 (Sept. 1990), 125– 141.

2. Jamali, N., Thati, P., and Agha, G. An actor-based architecture for customizing and controlling agent ensembles. IEEE Intelligent Systems 14, 2 (Apr. 1999), 38– 44.

GUL AGHA ( [e-mail]) is Director of the Open Systems Laboratory and a professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. He was Editor-in-Chief of ACM Computing Surveys 1999–2007.