SquadSmart — Hierarchical Planning and Coordinated Plan Execution for Squads of Characters

Abstract

This paper presents an application of Hierarchical Task Network (HTN) planning to a squad-based military simulation. The hierarchical planner produces collaborative plans for the whole squad in real time, generating the type of highly coordinated behaviours typical for armed combat situations involving trained professionals. Here, we detail the extensions to HTN planning necessary to provide real-time planning and subsequent collaborative plan execution. To make full hierarchical planning feasible in a game context we employ a planner compilation technique that saves memory allocations and speeds up symbol access. Additionally, our planner can be paused and resumed, making it possible to impose a hard limit on its computation time during any single frame. For collaborative plan execution we describe several synchronization extensions to the HTN framework, allowing agents to participate in several plans at once and to act in parallel or in sequence during single plans. Overall, we demonstrate that HTN planning can be used as an expressive and powerful real-time planning framework for tightly coupled groups of in-game characters.

Dynamic Expansion of Behaviour Trees

“…Goaloriented formalisms provide a declarative way for designers to express NPC behaviour, allowing for an underlying search algorithm to explore a potentially huge solution space. Hierarchical planning have been applied both in academic (Hoang, Lee-Urban, and Muñoz-Avila 2005) and industrial systems (Gorniak and Davis 2007), and it seems to point towards the next generation of more believable NPCs. Nevertheless, it still has to be found the way to educate game designers to be able to write domain descriptions and plan preconditions and postconditions.…”

Logical Agents for Language and Action

“…Unlike Soar, which is not primarily a planning framework, SquadSmart (Gorniak & Davis 2007) demonstrates how hierarchical task network planning can be used for multi-agent planning in games. An incremental algorithm ensures bounded computation time and an execution module synchronizes actions and copes with failures.…”