How do business organizations make decisions? What process do they follow in deciding how much to produce? And at what price? A behavioral theory of the firm is here explored. Using a specific type of duopoly, a model is written explicity as a computer program to deal with the complex theory implicit in the process by which businesses make decisions. This model highlights our need for more empirical observations of organizational decision‐making.
The DENDRAL Project was one of the first large-scale programs to embody the strategy of using detailed, task-specific knowledge about a problem domain as a source of heuristics, and to seek generality through automating the acquisition of such knowledge. This paper summarizes the major conceptual contributions and accomplishments of that project. It is an attempt to distill from this research the lessons that are of importance to artificial intelligence research and to provide a record of the final status of two decades of work.
A description is provided of EPAM‐III, a theory in the form of a computer program for simulating human verbal learning, along with a summary of the empirical evidence for its validity. Criticisms leveled against the theory in a recent paper by Barsalou and Bower are shown to derive largely from their misconception that EPAM‐III employed a binary, rather than n‐ary branching discrimination net. It is shown that Barsalou and Bower also failed to understand how the recursive structure of EPAM‐III eliminates the need to duplicate test nodes that are used to recognize subobjects, and how the possibility of redundant recognition paths controls the sensitivity of EPAM to noticing order. EPAM is also compared briefly with other theories of human discrimination and discrimination learning, including PANDEMONIUM‐like systems and dataflow nets.
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