Creating Complex Applications via Self-Adapting Autonomous Agents in an Intelligent System Framework

In this paper, we present a process, developed over years of practical commercial use, where applications accomplishing a wide variety of complex tasks are created from a common framework, through the use, recombination and iterative refinement of autonomous agents in a Multi-Agent Intelligent System. Driven by a need to solve real-world problems, our focus is to make businesses run more efficiently in an increasingly complex world of systems and software that must work together seamlessly. By listening closely to our customers' problems, we discovered points of commonality, as well as patterns of anomalies related to the flow of data through communication channels and data processing systems, include accounting, inventory, customer relationship management, scheduling systems and many more. We solved their problems through the creation of an Intelligent System, where we defined and implemented software agents that were highly configurable, responsive in real-time and useable in various settings. Autonomous agents adhere to a standard format of three major components: the goal or triggering criteria, the action, and the adaptation response. Agents run within a common Intelligent System framework and agent libraries provide a vast set of component behaviors to build applications from. Agents have one or more of the following component behaviors: sensory aware, geo-position aware, temporally aware, API aware, device aware, and many more. Additionally, there are manager-level agents whose goal is to keep the overall system in balance, through dynamic resource allocation on a system level. To prove the viability of this process, we present a variety of applications representing wide ranging behaviors, many with overlapping agents, created via this approach, all of which are in active commercial use. Finally, we discuss future enhancements toward self-organization, where end users express their requirements declaratively to solve larger business needs, resulting in the automatic instantiation of a solution specific intelligent system.