Cognitive modeling: knowledge, reasoning and planning for intelligent characters

Recent work in behavioral animation has taken impressive steps toward autonomous, self-animating characters for use in production animation and interactive games. It remains difficult, however, to direct autonomous characters to perform specific tasks. This paper addresses the challenge by introducing cognitive modeling. Cognitive models go beyond behavioral models in that they govern what a character knows, how that knowledge is acquired, and how it can be used to plan actions. To help build cognitive models, we develop the cognitive modeling language CML. Using CML, we can imbue a character with domain knowledge, elegantly specified in terms of actions, their preconditions and their effects, and then direct the character’s behavior in terms of goals. Our approach allows behaviors to be specified more naturally and intuitively, more succinctly and at a much higher level of abstraction than would otherwise be possible. With cognitively empowered characters, the animator need only specify a behavior outline or “sketch plan” and, through reasoning, the character will automatically work out a detailed sequence of actions satisfying the specification. We exploit interval methods to integrate sensing into our underlying theoretical framework, thus enabling our autonomous characters to generate action plans even in highly complex, dynamic virtual worlds. We demonstrate cognitive modeling applications in advanced character animation and automated cinematography.

[1]  D. Arijon,et al.  Grammar of Film Language , 1976 .

[2]  John McCarthy,et al.  SOME PHILOSOPHICAL PROBLEMS FROM THE STANDPOINT OF ARTI CIAL INTELLIGENCE , 1987 .

[3]  Craig W. Reynolds Flocks, herds, and schools: a distributed behavioral model , 1987, SIGGRAPH.

[4]  James F. Blinn,et al.  Where am I? What am I looking at? (cinematography) , 1988, IEEE Computer Graphics and Applications.

[5]  N. Magnenat-Thalmann,et al.  Synthetic actors in computer-generated 3D films , 1990 .

[6]  Raymond Reiter,et al.  The Frame Problem in the Situation Calculus: A Simple Solution (Sometimes) and a Completeness Result for Goal Regression , 1991, Artificial and Mathematical Theory of Computation.

[7]  John M. Snyder,et al.  Interval analysis for computer graphics , 1992, SIGGRAPH.

[8]  Hector J. Levesque,et al.  The Frame Problem and Knowledge-Producing Actions , 1993, AAAI.

[9]  Demetri Terzopoulos,et al.  Artificial fishes: physics, locomotion, perception, behavior , 1994, SIGGRAPH.

[10]  James A. Hendler,et al.  Readings in Planning , 1994 .

[11]  Joseph Bates,et al.  The role of emotion in believable agents , 1994, CACM.

[12]  Bruce Blumberg,et al.  Multi-level direction of autonomous creatures for real-time virtual environments , 1995, SIGGRAPH.

[13]  David Salesin,et al.  The virtual cinematographer: a paradigm for automatic real-time camera control and directing , 1996, SIGGRAPH.

[14]  Ken Perlin,et al.  Improv: a system for scripting interactive actors in virtual worlds , 1996, SIGGRAPH.

[15]  Hector J. Levesque,et al.  GOLOG: A Logic Programming Language for Dynamic Domains , 1997, J. Log. Program..

[16]  P. Maes,et al.  Old tricks, new dogs: ethology and interactive creatures , 1997 .

[17]  Barbara Hayes-Roth,et al.  Acting in Character , 2019, Creating Personalities for Synthetic Actors.

[18]  Claudio S. Pinhanez,et al.  Interval scripts: a design paradigm for story-based interactive systems , 1997, CHI.

[19]  Robert Trappl,et al.  Creating Personalities for Synthetic Actors , 1997, Lecture Notes in Computer Science.

[20]  John David Funge,et al.  Making them behave: cognitive models for computer animation , 1998 .

[21]  Xiaoyuan Tu,et al.  Artificial Animals for Computer Animation: Biomechanics, Locomotion, Perception, and Behavior , 1999, Lecture Notes in Computer Science.

[22]  John Funge,et al.  Representing Knowledge within the Situation Calculus Using Interval-Valued Epistemic Fluents , 1999, Reliab. Comput..

[23]  John David Funge,et al.  AI for Games and Animation: A Cognitive Modeling Approach , 1999 .