Two Paradigms Are Better Than One, and Multiple Paradigms Are Even Better

During the past half century, the field of artificial intelligence has developed a large number of theories, paradigms, technologies, and tools. Many AI systems are based on one dominant paradigm with a few subsidiary modules for handling exceptions or special cases. Some systems are built from components that perform different tasks, but each component is based on a single paradigm. Since people freely switch from one method of thinking or reasoning to another, some cognitive scientists believe that the ability to integrate multiple methods of reasoning is key to human-like flexibility. In his book

The Society of Mind

, Minsky (1986) presented an architecture for intelligence based on a society of heterogeneous agents that use different reasoning methods to solve different problems or different aspects of the same problem. That idea is intriguing, but it raises many serious issues: how to coordinate multiple agents, distribute tasks among them, evaluate their results, encourage agents that consistently produce good results, inhibit agents that produce misleading, irrelevant, or unfruitful results, and integrate all the results into a coherent response. The most difficult problem is to enable multiple heterogeneous agents, acting independently, to produce the effect of a single mind with a unified personality that can pursue and accomplish coherent goals. This article discusses ways of organizing a society of heterogeneous agents as an integrated system with flexible methods of reasoning, learning, and language processing.