IMPACTing SHOP: Putting an AI planner into a multi-agent environment
In this paper we describe a formalism for integrating the SHOP HTN planning system with the IMPACT multi-agent environment. We define the A-SHOP algorithm, an agentized adaptation of the SHOP planning algorithm that takes advantage of IMPACT's capabilities for interacting with external agents, performing mixed symbolic/numeric computations, and making queries to distributed, heterogeneous information sources (such as arbitrary legacy and/or specialized data structures or external databases). We show that A-SHOP is both sound and complete if certain conditions are met.
htn planning multi-agent systems heterogenous/distributed data