Abstract
Networked systems control is a known problem complicated because of the need to work with large groups of elementary agents. In many applications, it is impossible (or difficult) to validate agent movement models and provide sufficiently reliable control actions at the elementary system components level. The evolution of agent subgroups (clusters) leads to additional uncertainty in the studied control systems. We focus on new decentralized control methods based on local communications in complex multiagent dynamical systems. The problem of intelligence in a complex world is considered in connection to multiagent network systems, including a system named airplane with feathers, load balancing, and the multisensor-multitarget tracking problem. Moreover, the new result concerning the emergency of intelligence in a group of robots is provided. All these methods follow the paradigm of the direct reaction of each element (agent) of the system to its sensory data of current situation observations and the corresponding data from a limited number of its neighbors (local communications). At the same time, these algorithms achieve a mutual goal at the macro level. All of the considered emergent intelligence appearances inspire the necessity to “rethink” the previously recognized concepts of computability and algorithm in computer science.
Highlights
Appearing in the modern age, multifaceted problems encourage reconsidering the role of computer-based tools and methods in various applications
Two main directions in artificial intelligence evolution crystallize in the late twentieth century
The behavior and evolution of these bacteria communities are comprehended as natural examples of multiagent systems because the interactions between bacteria occur locally and bacterial density can be measured with no need to gather the whole data in one data center. These bacteria solve the global task using only local communications (QS) and, overall, this is an example of multiagent technologies
Summary
Appearing in the modern age, multifaceted problems encourage reconsidering the role of computer-based tools and methods in various applications. Reducing the clock cycle time (strobe impulse) and the distances between bits makes it impossible to isolate bits due to the quantum mechanical laws [1] It looks natural, in the future, to switch from primitive operations with the classical bits to operations outlined by specific micro-dynamic models operating with the related fragments. The agent notion may correspond to some dynamical model (a system component) or a specific set of models Without rigid centralization, these structures can successfully treat complex problems by splitting them into modules reallocating the agents’ dynamical partitions. These structures can successfully treat complex problems by splitting them into modules reallocating the agents’ dynamical partitions Such a system can effectively perform under significant uncertainties, demonstrating so-named “emergent intelligence”.
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