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arise automatically as a result of the recursive structure of the task and the continuous nature of the SRN's state space. Elman also introduces a new graphical technique for study- ing network behavior based on principal components analysis. He shows that sentences with multiple levels of embedding produce state space trajectories with an intriguing self- similar structure. The development and shape of a recurrent network's state space is the subject of Pollack's paper, the most provocative in this collection. Pollack looks more closely at a connectionist network as a continuous dynamical...

This highly accessible introduction to Lisp is suitable both for novices approaching their first programming language and experienced programmers interested in exploring a key tool for artificial intelligence research. The text offers clear, reader-friendly explanations of such essential concepts as cons cell structures, evaluation rules, programs as data, and recursive and applicative programming styles.
The treatment incorporates several innovative instructional devices, such as the use of function boxes in the first two chapters to visually distinguish functions from data, use of...

arise automatically as a result of the recursive structure of the task and the continuous nature of the SRN's state space. Elman also introduces a new graphical technique for study ing network behavior based on principal components analysis. He shows that sentences with multiple levels of embedding produce state space trajectories with an intriguing self similar structure. The development and shape of a recurrent network's state space is the subject of Pollack's paper, the most provocative in this collection. Pollack looks more closely at a connectionist network as a continuous dynamical...

This collection of papers covers research in the field of neural networks. Although summer school has always leaned towards cognitive science and artificial intelligence, the diverse backgrounds of participants reflects the broad spectrum of areas contributing to neural networks.