Using complex adaptive systems to investigate Aboriginal-tourism relationships in Purnululu National Park: exploring the role of capital

Resource management systems such as national parks are complex and dynamic with strong interdependencies between their human and ecological components. Their management has become more difficult as scale, impacts and consequences have increased and local communities have become increasingly involved. Increasing pressures from tourism have added to this management complexity. Complex adaptive systems thinking, and especially the metaphor of the adaptive cycle (Holling 2001), can potentially enhance our understanding of these resource systems, including national parks. The concept of the adaptive cycle can help understand changes over time in a system such as a national park

DynCNET: a negotiation and coordination protocol for dynamic task assignment.

Task assignment in Multi-Agent Systems is a complex coordination problem, especially in systems that operate under dynamic and changing conditions. Adaptive task assignment is used to handle these dynamic and changing circumstances. This technical document describes an adaptive task assignment protocol, DynCNET which is an extension of the Contract Net Protocol. In this document, the DynCNET protocol will be build step by step, starting from the Contract Net protocol. We will add dynamic task assignment, synchronization of abort messages and scope handling. The final result will be the DynCNET protocol with support for synchronization of abort messages and scope handling.

Systems And Methods For Parameter Dependent Riccati Equation Approaches To Adaptive Control

Systems and methods for adaptive control are disclosed. The systems and methods can control uncertain dynamic systems. The control system can comprise a controller that employs a parameter dependent Riccati equation. The controller can produce a response that causes the state of the system to remain bounded. The control system can control both minimum phase and non-minimum phase systems. The control system can augment an existing, non-adaptive control design without modifying the gains employed in that design. The control system can also avoid the use of high gains in both the observer design and the adaptive control law.Georgia Tech Research Corporatio

An Evolutionary Learning Approach for Adaptive Negotiation Agents

Developing effective and efficient negotiation mechanisms for real-world applications such as e-Business is challenging since negotiations in such a context are characterised by combinatorially complex negotiation spaces, tough deadlines, very limited information about the opponents, and volatile negotiator preferences. Accordingly, practical negotiation systems should be empowered by effective learning mechanisms to acquire dynamic domain knowledge from the possibly changing negotiation contexts. This paper illustrates our adaptive negotiation agents which are underpinned by robust evolutionary learning mechanisms to deal with complex and dynamic negotiation contexts. Our experimental results show that GA-based adaptive negotiation agents outperform a theoretically optimal negotiation mechanism which guarantees Pareto optimal. Our research work opens the door to the development of practical negotiation systems for real-world applications

The Use of Complex Adaptive Systems as a Generative Metaphor in an Action Research Study of an Organisation

Understanding the dynamic behaviour of organisations is challenging and this study uses a model of complex adaptive systems as a generative metaphor to address this challenge. The research question addressed is: How might a conceptual model of complex adaptive systems be used to assist in understanding the dynamic nature of organisations? Using an action research methodology, 6 Ai r Force internal management consulting teams were exposed to overlapping attributes of complex adaptive systems. The study shows that participants found the attributes valuable in understanding the dynamic nature of organisations; however they did present challenges for understanding. Despite being challenging to understand, using complex adaptive systems to understand organisations, particularly as dynamic systems, is of value

MORPH: A Reference Architecture for Configuration and Behaviour Self-Adaptation

An architectural approach to self-adaptive systems involves runtime change of system configuration (i.e., the system's components, their bindings and operational parameters) and behaviour update (i.e., component orchestration). Thus, dynamic reconfiguration and discrete event control theory are at the heart of architectural adaptation. Although controlling configuration and behaviour at runtime has been discussed and applied to architectural adaptation, architectures for self-adaptive systems often compound these two aspects reducing the potential for adaptability. In this paper we propose a reference architecture that allows for coordinated yet transparent and independent adaptation of system configuration and behaviour