Exploiting Agent Observability in Multi-Agent  System Programming

Along with direct interaction models, relying on message-based explicit  communication, indirect interaction models can play an important role for designing coordination strategies in Multi-Agent Systems (MAS).
Among indirect models, those based on agent observability such as over-sensing achieve coordination by letting agents observe and possibly reason about (each) others' actions and state.
In this paper we describe how over-sensing and, more generally, agent observability mechanism can be used in practice to program MAS in the context of artifact-based environments by exploiting the support provided by CArtAgO technology.