SENIOR MEMBER, IEEE, Statistics and Probability Program, Office of Naval Research, Arlington, VA 22217.
IEEE Trans Pattern Anal Mach Intell. 1982 May;4(5):485-92. doi: 10.1109/tpami.1982.4767292.
Computers and brains are modeled by finite and probabilistic automata, respectively. Probabilistic automata are known to be strictly more powerful than finite automata. The observation that the environment affects behavior of both computer and brain is made. Automata are then modeled in an environment. Theorem 1 shows that useful environmental models are those which are infinite sets. A probabilistic structure is placed on the environment set. Theorem 2 compares the behavior of finite (deterministic) and probabilistic automata in random environments. Several interpretations of Theorem 2 are discussed which offer some insight into some mathematical limits of machine intelligence.
计算机和大脑分别由有限和概率自动机建模。概率自动机被证明比有限自动机具有更强的表现力。观察到环境会影响计算机和大脑的行为。然后在环境中对自动机进行建模。定理 1 表明，有用的环境模型是那些无限集。在环境集合上放置一个概率结构。定理 2 比较了随机环境中有限（确定性）和概率自动机的行为。讨论了定理 2 的几种解释，这些解释为机器智能的一些数学限制提供了一些见解。
