| Abstract: | We define a Markovian Agent Model (MAM) as an analytical model
formed by a spatial collection of interacting Markovian Agents (MAs),
whose properties and behavior can be evaluated by numerical techniques.
MAMs have been introduced with the aim of providing a flexible and
scalable framework for distributed systems of interacting objects, where
both the local properties and the interactions may depend on the geographical
position. MAMs can be proposed to model biological inspired
systems since are suited to cope with the four common principles that
govern swarm intelligence: positive feedback, negative feedback, randomness,
multiple interactions. In the present work, we report some results
of a MAM model for WSN routing protocol based on swarm intelligence,
and some preliminary results in utilizing MAs for very basic
ACO benchmarks. |
