![](bg6.png)
Supervisory Agent (LSA) and Database Agent
(DBA). Complete description of all created agents
can be found in (Choinski and Senik, et al., 2010,
2011). MAXS layered architecture (Choinski and
Senik, 2011) presents openness and flexibility
which implies self management nature. It is a key
concept that satisfies dynamic conditions of the
integrated environment.
Self management functionality enables MAXS
platform agents to address both integrated
environmental issues and MAXS platform specific
events such as unexpected agent’s internal errors
or possible instabilities. Such approach allows fast
situation diagnosis and proper MAXS
counteraction. MAXS self management ability is a
fundamental feature that guards and preserves
system data integrity and quality. Each MAXS
agent shares similar capabilities making them more
compliant and consistent. Those capabilities are
the key concepts of the internal platform
architecture (Choinski and Senik, 2011).
To complete assigned tasks MAXS agents
reuses common set of fully customized and
concurrent behaviours (Choinski and Senik, 2010,
2011). Each one extends common mechanism of
knowledge sharing and management that utilizes
MAXS platform ontology.
MAXS reasoning model is based on the
subscription and notification mechanisms as well
as on the agent knowledge which is gradually
gathered over time from other platform agents.
6 CONCLUSIONS
The dynamic of the DCS is a normal situation
which has to be automatically handled in all
integration systems. Traditional approach to the
DCS integration seems to be insufficient to cover
most of the real life integration problems. Each
DCS grow and extend in time and the same should
happen with the integration system. Such system
must preserve an open architecture. It must be
scalable enough to follow the DCS extensions. The
solution to address those problems lays in adoption
of the proper methodology and architecture.
MAS based solution is the right choice that
meets the requirements of integration of the
dynamic environment. MAS DCS integration is
based on the proper resource knowledge
management. Presented ontology based knowledge
management is a generic mechanism. It helps
acquire all needed pieces of information based on
which analysis processes can be performed.
Ontology always gives a meaning to each tiniest
piece of information obtained from the integrated
system thus making it more understandable and
readable for both human user and agent entity.
ACKNOWLEDGEMENTS
This work was partially supported by the Polish
Ministry of Scientific Research and Higher
Education N N514 471539.
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