The Concept of Autonomy in Distributed Computation and Multi-Agent Systems

Abstract

The concept of autonomy is one of the central concepts in distributed computational systems, and in multi-agent systems in particular. With diverse implications in philosophy, social sciences and the theory of computation, autonomy is a rather complicated and somewhat vague notion. Most researchers do not discuss the details of this concept, but rather assume a general, common-sense understanding of autonomy in the context of computational multi-agent systems. In this chapter, we will review the existing definitions and formalisms related to the notion of autonomy. We re-introduce two concepts: relative autonomy and absolute autonomy. We argue that even though the concept of absolute autonomy does not make sense in computational settings, it is useful if treated as an assumed property of computational units. For example, the concept of autonomous agents facilitates more flexible and robust architectures. We adopt and discuss a new formalism based on results from the study of massively parallel multi-agent systems in the context of Evolvable Virtual Machines. We also present the architecture for building such architectures based on our multi-agent system KEA, where we use an extended notion of dynamic and flexibly linking. We augment our work with theoretical results from chemical abstract machine algebra for concurrent and asynchronous information processing systems. We argue that for open distributed systems, entities must be connected by multiple computational dependencies and a system as a whole must be subjected to influence from external sources. However, the exact linkages are not directly known to the computational entities themselves. This provides a useful notion and the necessary means to establish an autonomy in such open distributed systems.

A framework for facilitating cooperation in multi-agent systems

“…Generally there are two aspects in the agents' autonomy: the internal and external aspects. The internal aspect refers to self-governance of the agents, and the external aspect implies that agents' behaviour cannot be imposed by any other agent, and thus any interactions between agents must recognise the participants' autonomy [16]. Although using autonomous agents can model more realistic and dynamic situations, many studies in multi-agent systems have not considered agents as autonomous entities [17,18].…”