On the cost-complexity of multi-context systems
This work addresses cost efficiency for users of heterogeneous information-aggregation systems, but it appears incremental as it builds on existing non-monotonic multi-context systems frameworks.
The paper tackles the problem of high execution costs in multi-context systems by introducing cost-aware extensions and formulating cost-complexity for consistency and reasoning problems, resulting in an incremental cost-reducing algorithm for definite MCSs.
Multi-context systems provide a powerful framework for modelling information-aggregation systems featuring heterogeneous reasoning components. Their execution can, however, incur non-negligible cost. Here, we focus on cost-complexity of such systems. To that end, we introduce cost-aware multi-context systems, an extension of non-monotonic multi-context systems framework taking into account costs incurred by execution of semantic operators of the individual contexts. We formulate the notion of cost-complexity for consistency and reasoning problems in MCSs. Subsequently, we provide a series of results related to gradually more and more constrained classes of MCSs and finally introduce an incremental cost-reducing algorithm solving the reasoning problem for definite MCSs.