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This paper presents a conceptualization of information as related to the decision problems of the recipient. The orientation is toward a formal definition of behavioral elements in an individual's "purposeful state": specifically, these elements are his objectives, his valuation of each objective, his possible courses of action, the efficiency of each course of action in achieving each objective, and his probability of choice for each course of action. The amount of information in a purposeful state is explicitly defined in terms of the probabilities of choice of the available courses of action. The amount of information in a message is defined as the difference between the amount of information in the purposeful state following the message, and the amount of information in the purposeful state preceding the message. The amount of instruction in a purposeful state is defined in terms of the efficiencies of the available courses of action; and the amount of motivation is defined in terms of the values of the objectives. The amounts of instruction and motivation in a message are defined, just as information is, by comparing the amounts in a purposeful state before and after receipt of the message. The value of a purposeful state to an individual is defined as a function of the amount of information, the amount of instruction, and the amount of motivation in the state. This concept can be generalized to express the value of the state to some other individual. [ABSTRACT FROM AUTHOR]

In his paper, PEARCE presents a method for determining the stationary probabilities of a G/Mt/1 system, the service mechanism being such that it operates regardless of whether or not customers are present. This note is an attempt to correct his results. [ABSTRACT FROM AUTHOR]

The concept of a median in a weighted graph is generalized to a multi- median. Then, it is shown that the optimum distribution of p switching centers in a communication network is at a p-median of the corresponding weighted graph. The following related problem in highway networks is also considered: What is a minimum number of policemen that can be distributed in a highway network so that no one is farther away from a policeman than a given distanced? This problem is attacked by generating all vertex-coverings (externally stable sets) of a graph by means of a Boolean function defined over the vertices of a graph. Then this idea is extended to Boolean functions that generate all matchings, all factors, and all pos- sible subgraphs of G with given degrees. [ABSTRACT FROM AUTHOR]