Adaptation to Unexpected Changes: Where Ecosystems and Multi-Agent Systems Meet

UoM administered thesis: Phd

  • Authors:
  • Cesar Marin Pitalua


Unexpected changes occurring in complex and dynamic domains render supporting systems unsuited to the new conditions. Examples of such domains include business ecosystems, digital service ecosystems, manufacturing, transport, and city modelling. These are regarded as ecosystem domains. Multi-agent systems are seen as an appropriate technology for their support, yet they lack the required ability to adapt to unexpected changes.The research presented in this thesis aims to create a multi-agent system based in-silico model endowed with the capability of adaptation to unexpected changes occurring in ecosystem domains. The approach taken consists of applying adaptation properties of complex adaptive systems, such as natural ecosystems, to multi-agent systems to create one which can cope with unexpected changes.A dynamic agent-based ecosystem model called DAEM is formalised by combining characteristics of natural ecosystem and principles of adaptive multi-agent systems. A set of experiments is presented using a DAEM prototype to demonstrate its resilience to unexpected changes in a hypothetical ecosystem. A comparison is made against a simulated typical solution for showing how DAEM is more resilient to unexpected changes than the typical approach. This supports the claim of this thesis that DAEM represents a significant contribution to knowledge.A software embodiment of DAEM to drive adaptation in ecosystem domains is presented and placed in an execution context evaluated by two practical examples of ecosystem domains. These show how DAEM suggests interactions to the supporting system of the execution context, and incorporates taken decisions into the ecosystem regarding interactions with other individuals. This supports the claim that the DAEM software embodiment is suitable for providing adaptation support in ecosystem domains, thus representing another significant contribution of this thesis.The contributions to knowledge of this thesis are then a) a formal model of a dynamic agent-based ecosystem called DAEM; and b) a software embodiment of DAEM, called DAEM layer, to support adaptation in ecosystem domains. Future work includes further tests to analyse patterns and make estimations in existing ecosystems, among others.


Original languageEnglish
Awarding Institution
Award date1 Aug 2011