Simulating Teamwork and Information-Flow in Tactical Operations Centers using Multi-Agent Systems Yu Zhang Linli He Keith Biggers Dr. John Yen Dr. Thomas R.. Ioerger Department of Computer Science Texas A&M University College Station, Texas 77843-3112 979-845-5457 {yuzhang, linli, kbiggers, yen, ioerger}@cs.tamu.edu Keywords: Teamwork, Multi-Agent Systems, Distributed Artificial Intelligence, Knowledge Acquisition, Communication ABSTRACT: Battlefield simulations are playing an increasing role in training within the military. This is especially true for training staff officers in tactical operations centers (TOCs) at intermediate echelons like battalions and brigades. Currently, distributed battlefield simulations such as ModSAF and JANUS provide semi-autonomous control of entities (e.g. tanks), and smaller units (up to company size). However, larger units, such as battalions, are difficult to simulate because of the high level of human decision-making (i.e. in their own TOCs), and the coordination and exchange of information within and between battle staffs. Teamwork-oriented skills are needed for simulating these high-level types of information-oriented behaviors. In the University XXI project, we are developing a multi-agent architecture, called TaskableAgents, which focuses on dynamic plan execution and monitoring through the application of procedural knowledge, coupled with rule-based inference. Separate agents can have unique goals and task definitions, along with their own knowledge bases (with dynamic state information); they can communicate by sending messages to each other. In this paper, we describe how decision-making and behavior of a battalion TOC can be simulated in TaskableAgents through a decomposition of the activities into multiple agents that represent various functional areas within a battle staff. Then we show how communication actions between staff members (within the battalion TOC, and also interactions with the brigade TOC) can be generated from common operating procedures (tasks and methods) for each functional area. Extending our agent-based TOC model to incorporate multiple agents working collectively as a team allows for a more realistic simulation of the complex behaviors of (and interactions with) aggregates like battalions. This is important for enhancing the capabilities of large-scale simulations with features that better support the teamwork-focused and cooperation-oriented training of staff officers at higher echelons. 1. Introduction Teamwork is an essential element of training. While soldiers and other members of the Armed Forces are taught basic skills for individual tasks, such as how to operate various pieces of equipment like communications devices, weapons, vehicles, etc., and procedures, such as making requests and reports or setting up or mobilizing camps, it is critical for them to learn how to bring these individual abilities together to produce coordinated teamwork that enables the unit to accomplish its mission. Each member typically plays a role in the team, and they must learn how their individual actions fit into the context of the whole team to be maximally effective. This requires that they have a chance to refine their communication and coordination skills, practice group decision-making procedures, and achieve a general understanding (mental model) of each others' responsibilities and capabilities. In the military, the team structure is very hierarchical and extends upward through many echelons, forming many levels of teamwork. A particularly important example of teamwork is within tactical operations centers (TOCs). In mid-level echelons like battalions and brigades, TOCs consist of a variety of staff officers for areas including intelligence (S2), maneuvers (S3), fire-support (FSO), air-defense (ADO), engineering (ENGR), and logistics. Each of the staff members plays a unique role; however, their primary goal as a group is to support the decision-making of the commander. Individual activities include collecting information (about the enemy) and assimilating it into a common relevant picture (situation assessment), tracking friendly assets and combat strength, battle-damage