Magazine article AI Magazine

Human-Level AI's Killer Application Interactive Computer Games

Magazine article AI Magazine

Human-Level AI's Killer Application Interactive Computer Games

Article excerpt

Over the last 30 years, research in AI has fragmented into more and more specialized fields, working on more and more specialized problems, using more and more specialized algorithms. This approach has led to a long string of successes with important theoretical and practical advancements. However, these successes have made it easy for us to ignore our failure to make significant progress in building human-level AI systems. Human-level AI systems are the ones that you dreamed about when you first heard of AI: HAL from 2001, A Space Odyssey; DATA from Star Trek; or CP30 and R2D2 from Star Wars. They are smart enough to be both triumphant heroes and devious villains. They seamlessly integrate all the human-level capabilities: real-time response, robustness, autonomous intelligent interaction with their environment, planning, communication with natural language, commonsense reasoning, creativity, and learning.

If this is our dream, why isn't any progress being made? Ironically, one of the major reasons that almost nobody (see Brooks et al. [2000] for one high-profile exception) is working on this grand goal of AI is that current applications of AI do not need full-blown human-level AI. For almost all applications, the generality and adaptability of human thought is not needed--specialized, although more rigid and fragile, solutions are cheaper and easier to develop. Unfortunately, it is unclear whether the approaches that have been developed to solve specific problems are the right building blocks for creating human-level intelligence. The thesis of this article is that interactive computer games are the killer application for human-level AI. They are the application that will need human-level AI. Moreover, they can provide the environments for research on the right kinds of problem that lead to the type of incremental and integrative research needed to achieve human-level AI.

Computer-Generated Forces

Given that our personal goal is to build human-level AI systems, we have struggled to find the right application for our research that requires the breadth, depth, and flexibility of human-level intelligence. In 1991, we found computer-generated forces for large-scale distributed simulations as a potential application. Effective military training requires a complete battle space with tens if not hundreds or thousands of participants. The real world is too expensive and dangerous to use for continual training, and even simulation is prohibitively expensive and cumbersome when fully manned with humans. The training of 4 pilots to fly an attack mission can require over 20 planes plus air controllers. The military does not even have a facility with 20 manned simulators, and if it did, the cost in personnel time for the other pilots and support personnel to train these four pilots would be astronomical. To bypass these costs, computer-generated forces are being developed to populate these simulations. These forces must integrate many of the capabilities we associate with human behavior--after all, they are simulating human pilots. For example, they must use realistic models of multiple sensing modalities, encode and use large bodies of knowledge (military doctrine and tactics), perform their missions autonomously, coordinate their behavior, react quickly to changes in the environment, and dynamically replan missions. Together with researchers at the University Southern California Information Sciences Institute and Carnegie Mellon University, we set off to build human-level AIs for military air missions (Tambe et al. 1995). In 1997, we successfully demonstrated fully autonomous simulated aircraft (Jones et al. 1999), and research and development continues on these systems by Soar Technology, Inc. Although computer-generated forces are a good starting application for developing human-level AI, there are extremely high costs for AI researchers to participate in this work. It requires a substantial investment in time and money to work with the simulation environments and to learn the extensive background knowledge, doctrine, tactics, and missions. …

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