Richard L. Frost

Vector quantizers with direct sum codebooks

The use of direct sum codebooks to minimize the memory requirements of vector quantizers is investigated. Assuming arbitrary fixed partitions, necessary conditions for minimum distortion codebooks are derived, first for scalar codebooks, assuming mean-squared error distortion, and then for vector codebooks and a broader class of distortion measures. An iterative procedure is described for designing locally optimal direct sum codebooks. Both optimal and computationally efficient suboptimal encoding schemes are considered. It is shown that although an optimal encoding can be implemented by a sequential encoder, the complexity of implementing optimal stagewise partitions generally exceeds the complexity of an exhaustive search of the direct sum codebook. It is also shown that sequential nearest-neighbor encoders can be extremely inefficient. The M-search method is explored as one method of improving the effectiveness of suboptimal sequential encoders. Representative results for simulated direct sum quantizers are presented. >

A theory of satisficing decisions and control

The existence of an optimal control policy and the techniques for finding it are grounded fundamentally in a global perspective. These techniques can be of limited value when the global behaviour of the system is difficult to characterize, as it may be when the system is nonlinear, when the input is constrained, or when only partial information is available regarding system dynamics or the environment. Satisficing control theory is an alternative approach that is compatible with the limited rationality associated with such systems. This theory is extended by the introduction of the notion of strong satisficing to provide a systematic procedure for the design of satisficing controls. The power of the satisficing approach is illustrated by applications to representative control problems.

A cooperative multi-agent approach to free flight

The next generation of air traffic control will require automated decision support systems in order to meet safety, reliability, flexibility, and robustness demands in an environment of steadily increasing air traffic density. Automation is most readily implemented in free flight, the segment of flight between airports. In this environment, centralized control is impractical, and on-board distributed decision making is required. To be effective, such decision making must be cooperative. Satisficing game theory provides a theoretical framework in which autonomous decision makers may coordinate their decisions. The key feature of the theory is that, unlike conventional game theory which is purely egotistic in its structure, it provides a natural mechanism for decision makers to form their preferences by taking into consideration the preferences of others. In this way, a controlled form of conditional altruism is possible, such that agents are able to compromise so that every decision maker receives due consideration in a group environment. Simulations demonstrate that reliable performance can be achieved with densities on the order of 50 planes per ten thousand square miles.

A Satisficing Approach to Aircraft Conflict Resolution

Future generations of air traffic management systems may give appropriately equipped aircraft the freedom to change flight paths in real time. This would require a conflict avoidance and resolution scheme that is both decentralized and cooperative. We describe a multiagent solution to aircraft conflict resolution based on satisficing game theory. A key feature of the theory is that satisficing decision makers form their preferences by taking into consideration the preferences of others, unlike conventional game theory that models agents that maximize self-interest metrics. This makes possible situational altruism, a sophisticated form of unselfish behavior in which the preferences of another agent are accommodated provided that the other agent will actually take advantage of the sacrifice. This approach also makes possible the creation of groups in which every decision maker receives due consideration. We present simulation results from a variety of scenarios in which the aircraft are limited to constant-speed heading-change maneuvers to avoid conflicts. We show that the satisficing approach results in behavior that is attractive both in terms of safety and performance. The results underscore the applicability of satisficing game theory to multiagent problems in which self-interested participants are inclined to cooperation.

On the accuracy of memory reference models

This paper presents a new method of quantifying and visualizing the locality characteristics of any reference stream. After deriving a locality function, we show the correspondence between features of the locality function and common low-level program structures. We then apply the method to determine the locality characteristics of reference streams generated by a variety of synthetic models. These characteristics are shown to be substantially different from those of the reference trace used to determine the parameters of the models. We conclude that these synthetic models have serious inadequacies for evaluating the performance of memory hierarchies.

Locality as a visualization tool

This brief contribution introduces a method of quantifying the locality in a given reference sequence and visually representing it as a three dimensional surface. We explore some of the properties of this formulation of locality and show the correlation between graphical features and specific reference patterns. The utility of our formulation of locality is demonstrated through two of its potential applications as a visualizations tool: characterizing and summarizing workload locality, and evaluating the effectiveness of benchmark programs in exercising memory hierarchies.

Residual vector quantizers with jointly optimized code books

Publisher Summary This chapter discusses the basic principles of minimum distortion quantization; both scalar and vector quantizers are considered. It also discusses the residual quantizer (RQ) structure and an alternative RQ representation used in subsequent analysis called the “equivalent single-stage quantizer” and the methods to optimize scalar RQs. The chapter also presents a derivation of necessary conditions for minimum distortion. In the chapter, the problem of encoding complexity is also considered, and the difficulties associated with tree-structured encoders for RQ are described and illustrated. A modified RQ alphabet based on stagewise reflection symmetry and termed reflected RQ (rRQ) is introduced. Further, comparison is drawn between the distortion and complexity of the exhaustive search vector quantizers, the unoptimized RQ, optimized RQ, and rRQ on a variety of synthetic and natural sources.

A utility approach to multi-agent coordination

Addresses the problem of positioning a group of autonomous but coordinating mobile robots into a specified spatial configuration, with each position occupied by a single robot. Specifically, we assume that there is no central controller or inter-agent communication, and require that the robots must move into position without collision or unnecessary delay. We present an approach to this problem based on praxeic utility theory and evaluate its effectiveness, with particular emphasis on computational feasibility.

Model predictive satisficing fuzzy logic control

Model-predictive control, which is an alternative to conventional optimal control, provides controller solutions to many constrained and nonlinear control problems. However, even when a good model is available, it may be necessary for an expert to specify the relationship between local model predictions and global system performance. We present a satisficing fuzzy logic controller that is based on a receding control horizon, but which employs a fuzzy description of system consequences via model predictions. This controller considers the gains and losses associated with each control action, is compatible with robust design objectives, and permits flexible defuzzifier design. We demonstrate the controllers application to representative problems from the control of uncertain nonlinear systems.

Social utility Functions-part II: applications

Social utilities account for agent preferences and, thus, can characterize complex interrelationships, such as cooperation, compromise, negotiation, and altruism, that can exist between agents. Satisficing game theory, which is based on social utilities, offers a framework within which to design sophisticated multiagent systems. Key features of this approach are: a) an N-agent system may be represented by a 2N-dimensional Bayesian network, called a praxeic network; b) the theory accommodates a notion of situational altruism (a willingness to defer to others in a controlled way if so doing would actually benefit others under the condition that others wish to take advantage of such largesse); and c) satisficing games admits a protocol for effective negotiation between agents who, though interested in their own welfare, are also willing to give some deference to others. Three applications are presented. The first two involve well-known two-person games: the Prisoners Dilemma and the Battle of the Sexes, and the third is a simulated uninhabited aerial vehicle scenario.