Flocking Behaviour: Agent-Based Simulation and Hierarchical Leadership

We have studied how leaders emerge in a group as a consequence of interactions among its members. We propose that leaders can emerge as a consequence of a self-organized process based on local rules of dyadic interactions among individuals. Flocks are an example of self-organized behaviour in a group and properties similar to those observed in flocks might also explain some of the dynamics and organization of human groups. We developed an agent-based model that generated flocks in a virtual world and implemented it in a multi-agent simulation computer program that computed indices at each time step of the simulation to quantify the degree to which a group moved in a coordinated way (index of flocking behaviour) and the degree to which specific individuals led the group (index of hierarchical leadership). We ran several series of simulations in order to test our model and determine how these indices behaved under specific agent and world conditions. We identified the agent, world property, and model parameters that made stable, compact flocks emerge, and explored possible environmental properties that predicted the probability of becoming a leader.Flocking Behaviour; Hierarchical Leadership; Agent-Based Simulation; Social Dynamics

Large Flocks of Small Birds: on the Minimal Size of Population Protocols

Population protocols are a well established model of distributed computation by mobile finite-state agents with very limited storage. A classical result establishes that population protocols compute exactly predicates definable in Presburger arithmetic. We initiate the study of the minimal amount of memory required to compute a given predicate as a function of its size. We present results on the predicates x >= n for n in N, and more generally on the predicates corresponding to systems of linear inequalities. We show that they can be computed by protocols with O(log n) states (or, more generally, logarithmic in the coefficients of the predicate), and that, surprisingly, some families of predicates can be computed by protocols with O(log log n) states. We give essentially matching lower bounds for the class of 1-aware protocols

Data recording and analysis of American sign language

American Sign Language (ASL) is a form of communication that is used by the Deaf. It consists of hand shapes and gestures to express words and phrases. Translators on the market today consist of interpreting a simple form of ASL known as finger spelling. In order to develop a more effective translator, instrumentation was developed utilizing a Flock of Birds and Cyberglove system to record in hand shapes and movements in a LabVIEW environment. Experimentation done included reading in data and subjectively analyzing the data recorded for accuracy. Initial results have show that the instrumentation worked and data was recorded successfully

Development and optimisation of tracking methods to facilitate movement ecology research for the conservation management of black cockatoos in Western Australia

The three black cockatoo species endemic to south-west Western Australia – Carnaby’s cockatoo (Calyptorhynchus latirostris), Baudin’s cockatoo (C. baudinii) and forest red-tailed black cockatoo (C. banksii naso) are threatened and have Recovery Plans guiding conservation efforts. Threats include habitat loss due to land clearing for urban, agricultural and industrial development; competition with other species for nest hollows; poaching; disease; vehicle-strike and illegal shooting. This research built on previous black cockatoo research with an overall aim to develop and validate reliable methods to track all three species, to gain insight into their movement, distribution, habitat use, activity and behaviour. In an initial proof of concept trial, we attached tail-mounted tags to two Baudin’s cockatoos. Both birds were successfully tracked for several months after release, demonstrating satellite telemetry can be used to locate and track forest species. We then developed a double-tag mounting protocol to attach a tail-mounted ARGOS PTT satellite tag and back-mounted solar-powered UvA-BiTS GPS tag to captive black cockatoos. The combination of UvA-BiTS back mount and ventral tail mounted Telonics tags was the best tolerated and provided excellent GPS and ARGOS satellite location data with no interference between the two types of tag. The focus then moved to the development of an automated classifier tool that used accelerometer data from UvA-BiTS GPS tags to remotely identify behaviours and calculate activity budgets. Using accelerometer data from 15 birds post-release, we determined black cockatoos spend most of their time at rest, interspersed with foraging activity through the day and some movement between roost sites and feeding habitat. To maximise the retention time of tail-mounted tags, the tail feather life span and time of moulting was studied using moulted tail feathers from captive cockatoos and tagged bird post-release. Captive cockatoos had a mean feather lifespan of 410 days, suggesting tail feathers do not always moult annually. Peak tail feather moulting occurs from December to March, the non-breeding period. The optimal time to attach tail mounted tags is from May to September. The development and optimisation of tracking methodologies for use on black cockatoos has facilitated the tracking of all three species in the wild. This research has provided data which have enabled identification of key roosting, foraging and breeding habitat and determination of flock movement patterns and habitat use at a landscape scale across the species’ distribution ranges. This information is being used to guide black cockatoo conservation management in relation to habitat protection and restoration

Architectural Considerations for Single Operator Management of Multiple Unmanned Aerial Vehicles

Recently, small Unmanned Aircraft Systems (UAS) have become ubiquitous in military battlefield operations due to their intelligence collection capabilities. However, these unmanned systems consistently demonstrate limitations and shortfalls with respect to size, weight, range, line of sight and information management. The United States Air Force Unmanned Aircraft Systems Flight Plan 2009-2047 describes an action plan for improved UAS employment which calls out single operator, multi-vehicle mission configurations. This thesis analyzes the information architecture using future concepts of operations, such as biologically-inspired flocking mechanisms. The analysis and empirical results present insight into the engineering of single-operator multiple-vehicle architectures

Study of the trajectories of visually guided movement of unimanual and bimanual tasks

Restitution of upper limb mobility following stroke is one of the major challenges facing clinicians in the country today. The complexity of performing skilled tasks with fine movements makes restitution of mobility all the more complex for rehabilitation specialists. Although several techniques have been evolved for, limited success with transfer of training from the clinical environment to functional performance clearly indicates a need for research and development in the area of upper extremity rehabilitation. Bimanual coordination has recently surfaced as a novel and effective way to fast and lasting recovery. The success of bimanually coordinated training encourages a better understanding of the underlying neural, physiological and engineering principles involved which in turn would result in improved treatments for people with hemiparesis. An apparatus developed in this project enables such an understanding, by successfully being able to collect, record and analyze the movement trajectories of both the hands simultaneously with a high degree of accuracy

A Sign-to-Speech Translation System

This thesis describes sign-to-speech translation using neural networks. Sign language translation is an interesting but difficult problem for which neural network techniques seem promising because of their ability to adjust to the user\u27s hand movements, which is not possible to do by most other techniques. However, even using neural networks and artificial sign languages, the translation is hard, and the best-known system, that of Fels & Hinton (1993), is capable of translating only 66 root words and 203 words including their conjugations. This research improves their results to 790 root signs and 2718 words including their conjugations while preserving a high accuracy (i.e., over 93 %) in translation. The use of matcher neural networks (Revesz 1989, 1990) and asymmetric Hamming distances are the key sources of improvement. This research aims at providing a means of communication for deaf people. Adviser: Peter Z. Reves