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ARTICLES:
The Swarm Computing Approach to Business Intelligence
Issue: 4:3 (The fifteenth issue)
We have proposed to use some features of swarm behaviours in modelling business
processes. Due to these features we deal with a propagation of business processes in all
accessible directions. This propagation is involved into our formalization instead of
communicating sequential processes. As a result, we have constructed a business process
diagram language based on the swarm behavior and an extension of that language in the
form of reflexive management language.
processes. Due to these features we deal with a propagation of business processes in all
accessible directions. This propagation is involved into our formalization instead of
communicating sequential processes. As a result, we have constructed a business process
diagram language based on the swarm behavior and an extension of that language in the
form of reflexive management language.
Logics for Physarum Chips
Issue: 5:1 (The seventeenth issue)
The paper considers main features of two groups of logics for biological
devices, called Physarum Chips, based on the plasmodium. Let us recall that
the plasmodium is a single cell with many diploid nuclei. It propagates
networks by growing pseudopodia to connect scattered nutrients (pieces of
food). As a result, we deal with a kind of computing. The first group of logics
for Physarum Chips formalizes the plasmodium behaviour under conditions of
nutrient-poor substrate. This group can be defined as standard storage
modification machines. The second group of logics for Physarum Chips covers
the plasmodium computing under conditions of nutrient-rich substrate. In this
case the plasmodium behaves in a massively parallel manner and propagates in
all possible directions. The logics of the second group are unconventional and
deal with non-well-founded data such as infinite streams.
devices, called Physarum Chips, based on the plasmodium. Let us recall that
the plasmodium is a single cell with many diploid nuclei. It propagates
networks by growing pseudopodia to connect scattered nutrients (pieces of
food). As a result, we deal with a kind of computing. The first group of logics
for Physarum Chips formalizes the plasmodium behaviour under conditions of
nutrient-poor substrate. This group can be defined as standard storage
modification machines. The second group of logics for Physarum Chips covers
the plasmodium computing under conditions of nutrient-rich substrate. In this
case the plasmodium behaves in a massively parallel manner and propagates in
all possible directions. The logics of the second group are unconventional and
deal with non-well-founded data such as infinite streams.
