Spatial orientation behavior is universal among animals, but its neuronal basis is poorly understood. The main objective of the present study was to identify candidate patterns of neuronal connectivity (motifs) for two widely recognized classes of spatial orientation behaviors: hill climbing, in which the organism seeks the highest point in a spatial gradient, and goal seeking, in which the org...

Distributed hill-climbing algorithms are a powerful, practical technique for solving large Distributed Constraint Satisfaction Problems (DSCPs) such as distributed scheduling, resource allocation, and distributed optimization. Although incomplete, an ideal hill-climbing algorithm finds a solution that is very close to optimal while also minimizing the cost (i.e. the required bandwidth, processi...

We use directed search techniques in the space of computer programs to learn recursive sequences of positive integers. Specifically, the integer sequences of squares, x; cubes, x; factorial, x!; and Fibonacci numbers are studied. Given a small nite pre x of a sequence, we show that three directed searches|machine-language genetic programming with crossover, exhaustive iterative hill climbing, a...

The apparent slope of a hill, termed geographical slant perception, is overestimated in explicit awareness. Proffitt (2006) argued that overestimation allows individuals to manage their locomotor resources. Increasing age, fatigue, and wearing a heavy back pack will reduce the available resources and result in steeper reports for a particular hill. In contrast, Durgin and colleagues have propos...

Several parameter tables for PID controllers are known from the literature, control of time-delayed systems. The best is that Ziegler and Nichols, but there others also. In this publication, a table presented minimizes quality criteria IAE, ITAE ISE systems can be identified with PTn controller output limitation also taken into account. Since it very computationally intensive to calculate these...

Received (received date) Revised (revised date) Reinforcement learning is one of the more attractive machine learning technologies, due to its unsupervised learning structure and ability to continually learn even as the operating environment changes. Additionally, by applying reinforcement learning to multiple cooperative software agents (a multi-agent system) not only allows each individual ag...

This paper reports on the use of search techniques to help optimise a case-based reasoning (CBR) system for predicting software project effort. A major problem, common to ML techniques in general, has been dealing with large numbers of case features, some of which can hinder the prediction process. Unfortunately searching for the optimal feature subset is a combinatorial problem and therefore N...

Adults are encouraged to participate in aerobic activities that involve large muscle groups and are rhythmic in nature. Cycling and stair climbing are both activities that fit this recommendation and have been shown to enhance overall fitness and health. Further, cycling and stepping are currently prescribed during lower extremity orthopedic rehabilitation. These activities also help to reduce ...

This paper presents a method for pattern discovery based on viewpoints and feature set patterns. The representation for pattern components accommodates in a fully general way the taxonomic relationships that may exist between interval classes. A heuristic probabilistic hill climbing algorithm is developed to rapidly direct the search towards interesting patterns. The method can be used for sing...

Cohesive subgroups have always represented an important construct for sociologists who study individuals and organizations. In this article, I apply recent advances in the statistical modell ing of social network data to the task of identifying cohesive subgroups from social network data. Further, through simulated data, I describe a process for obtaining the probability that a given sample of ...