ITM Web of Conferences
Volume 3, 2014ACTIMS 2014 – Activity-Based Modeling & Simulation 2014
|Number of page(s)||16|
|Section||Intelligent and Biological Systems|
|Published online||02 December 2014|
Context and attention in activity-based intelligent systems
1 Dunip Technologies, LLC, Colorado, USA
2 ACIMS, University of Arizona, Tucson, AZ, USA
a Corresponding author: firstname.lastname@example.org
Complex natural systems are natural systems that display strong emergent behavior. Adaptive agents in a resource limited environment optimize their behavior by processing only the most relevant information, i.e., activating the most germane components, learned or evolved from previous experience, thereby responding optimally with least expenditure of energetic resources. A new class of artificial systems known as Resource-constrained Complex Intelligent Dynamical Systems (RCIDS) aim to capture this agent behavior and how these agents switch their attention from one object/subject to the next by way of using activity-aware algorithms in a multi-level hierarchy. In this article, we provide an overview of adaptive systems based on RCIDS. The activity manifested by the resource-constrained agents can be captured towards engineering an intelligent system capable of switching attention. We will discuss the relationship between Activity, Systems Theory, Emergent Behavior, and Second Order Cybernetics, and establish that an activity-based intelligent system (ABIS) can be engineered using Discrete Event Systems (DEVS) formalism through its Levels of Systems Specification. We elaborate on the multi-faceted nature of activity and describe how activity is positioned at a higher level of abstraction than the agent, thereby, abstracting away the agent architecture underneath by making it completely transparent in the same way that Minsky’s Society of Mind abstracts away neurons, axons, and synapses to compose a brain-like system of agents and k-lines. We present the theory behind ABIS, the context-agnostic behavior of algorithms implemented within agents and various issues that need to be addressed to engineer an ABIS.
© Owned by the authors, published by EDP Sciences, 2014
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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