Human Behavior Models for Agents in Simulators and Games: Part II: Gamebot Engineering with PMFserv

Abstract

Many producers and consumers of legacy training simulator and game environments are beginning to envision a new era where psycho-socio-physiologic models could be interoperated to enhance their environments' simulation of human agents. This paper explores whether we could embed our behavior modeling framework (described in the companion paper, Part 1) behind a legacy first person shooter 3D game environment to recreate portions of the Black Hawk Down scenario. Section 1 amplifies the interoperability needs and challenges confronting the field, presents the questions that are examined, and describes the test scenario. Sections 2 and 3 review the software and knowledge engineering methodology, respectively, needed to create the system and populate it with bots. Results (Section 4) and discussion (Section 5) reveal that we were able to generate plausible and adaptive recreations of Somalian crowds, militia, women acting as shields, suicide bombers, and more. Also, there are specific lessons learned about ways to advance the field so that such interoperabilities will become more affordable and widespread. Philadelphia, PA 19104-6315, USA. e-mail: barryg@seas.upenn.edu ABSTRACT Many producers and consumers of legacy training simulator and game environments are beginning to envision a new era where psych-socio-physiologic models could be interoperated to enhance their environments' simulation of human agents. This article explores whether we could embed our behavior modeling framework (described in Part I) behind a legacy first person shooter 3-D game environment to recreate portions of the Black Hawk Down scenario. Section One amplifies on the inter-operability needs and challenges confronting the field, presents the questions that are examined, and describes the test scenario. Sections 2 and 3 review the software and knowledge engineering methodology, respectively, needed to create the system and populate it with bots. Results (Section 4) and discussion (Section 5) reveal that we were able to generate plausible and adaptive recreations of Somalian crowds, militia, women acting as shields, suicide bombers, and more. Also, there are specific lessons learned about ways to advance the field so that such inter-operabilities will become more affordable and widespread.

Agent-based simulation of episodic criminal behaviour1

“…Agent models for human-like behaviour incorporating more cognitive and social aspects (such as trust and theory of mind) are described in [27,28,29]. These references focus on the internal architecture of an agent, and the applications aimed at are mainly in the area of games and virtual reality.…”

An embeddable testbed for insurgent and terrorist agent theories: InsurgiSim

“…PMFserv is in use by an intelligence agency to model diplomatic decisions of world leaders for which it has passed statistical correspondence tests showing it is significantly in agreement with their decision-making: see Silverman et al [18]. PMFserv has also reached the level where it can realistically simulate ethno-political conflicts among regional leaders and their followers vying over control of contested resources and assets (published validation studies for application in the Far East, MidEast Africa, and domestically are in Silverman et al [16,17,19]. FactionSim makes use of PMFserv to run both leader and follower agents and to use their micro-decision making to study group dynamics and how macro-behaviors and new equilibria autonomously emerge.…”

Human terrain data - what should we do with it?

“…The talk will overview the IDE and explain the knowledge engineering methodology we follow to assure the highest internal validity of the profile of a given agent. Silverman et al (2006bSilverman et al ( , 2007b.…”