17905930
Evaluating Team Performance at the Edge of Chaos
We introduce a concise approach to teamwork evaluation on multiple levels – dealing with agent’s behaviour spread and multi-agent coordination potential, and abstracting away the team decision process. The presented quantitative information-theoretic methods measure behavioural and epistemic entropy, and detect phase transitions – the edge of chaos – in team performance. The techniques clearly identify under-performing states, where a change in tactics may be warranted. This approach is a step towards a unified quantitative framework on behavioural and belief dynamics in complex multi-agent systems.
487167
On Self-organising Diagnostics in Impact Sensing Networks
Structural health management (SHM) of safety-critical structures requires multiple capabilities: sensing, assessment, diagnostics, prognostics, repair, etc. This paper presents a capability for self-organising diagnosis by a group of autonomous sensing agents in a distributed sensing and processing SHM network. The diagnostics involves acoustic emission waves emitted as a result of a sudden release of energy during impacts and detected by the multi-agent network. Several diagnostic techniques identifying the nature and severity of damage at multiple sites are investigated, and the self-organising maps (Kohonen neural networks) are shown to outperform the standard k-means algorithm in both time- and frequency domains.
17885591
Towards Adaptive Clustering in Self-monitoring Multi-agent Networks
A Decentralised Adaptive Clustering (DAC) algorithm for self-monitoring impact sensing networks is presented within the context of CSIRO-NASA Ageless Aero-space Vehicle project. DAC algorithm is contrasted with a Fixed-order Centralised Adaptive Clustering (FCAC) algorithm, developed to evaluate the comparative performance. A number of simulation experiments is described, with a focus on the scalability and convergence rate of the clustering algorithm. Results show that DAC algorithm scales well with increasing network and data sizes and is robust to dynamics of the sensor-data flux.
15572586
Complexity metrics for self-monitoring impact sensing networks
In this paper we describe novel metrics measuring complexity in self-organising networks. The metrics are investigated within the context of decentralised inspections, developed and implemented as part of the joint CSIRO-NASA Ageless Aerospace Vehicle (AAV) research project. The AAV Concept Demonstrator is a hardware multi-cellular sensing and communication network which is expected to detect and react to multiple impacts, without any centralised controllers. We present an extension of an ant colony optimisation algorithm, using an adaptive dead reckoning scheme and producing robust and reconfigurable minimum spanning trees connecting autonomous AAV cells. We then introduce a new metric detecting emergence through irregularities in the multi-agent communications, and contrast it with conventional macro-level ("global-view") graph-theoretic metrics.
16423538
On Decentralised Clustering in self-monitoring networks
A Decentralised Adaptive Clustering (DAC) algorithm for multiagent networks is contrasted with a Fixed-order Centralised Adaptive Clustering algorithm (FCAC). The clustering is done on sensor readings detected within a self-monitoring impact sensing network. Simulation results show that DAC algorithm scales well with increasing network and data sizes and in some cases outperforms FCAC algorithm. While the common-sense intuition suggests that centralised algorithm is always superior, we support the simulation results with a simple counter-example.
15078369
Self-organising impact boundaries in ageless aerospace vehicles
Self-monitoring, self-repairing aerospace vehicles require modular, flexible and adaptive sensing and communication networks. In general, a modular (multi-cellular) sensing and communication network is expected to detect and react to impact location, energy and damage over a wide range of impacts. It is critical that global response emerges as a result of interactions involving transfer of information embedded locally, avoiding single points-of-failure. This work presents mechanisms ensuring self-organisation of autonomous cells into robust and continuously connected impact boundaries. The spatiotemporal stability is demonstrated for a variety of cell shapes in a dynamic environment with varying energy dissipation and damage probability models.
42651
Analytical design of maximally flat FIR fractional Hilbert transformers
Recently, the classical Hilbert transformer is generalized into the fractional Hilbert transformer which could be implemented optically. This modification of the Hilbert transform adds an additional degree of freedom on the Hilbert transformer and improves the performance of the transform. In this paper, the design of FIR filters fractional Hilbert transformer is proposed. The FIR filters are designed in the maximally flat sense. The impulse responses of the filters are uniquely solved and expressed in simple analytic forms. The impulse responses can be exactly expressed as fixed point binary values. The resulting frequency responses approximate the ideal one very well in the middle-frequency band. Efficient hardware realization structures are obtained based on the symmetric properties of the impulse responses. Several design examples with various transform parameters and various filter orders are presented. Some examples of 1-D/2-D edge detection are given. The examples show that the proposed FIR filter can enhance the selected edges very efficiently.
8428215
A Tennis Video Indexing Approach Through Pattern Discovery in Interactive Process
Tennis game is a mutual and interactive process between the two opponents, and audiences are usually interested in how the players oppose and compete with each other. However, previous works on tennis video indexing are mainly based on analyses of player’s behavior, such as movement and gesture, and seldom provide information of the match process. In this paper, a novel approach is proposed for tennis video indexing by mining the salient patterns in the match process. The match is first characterized by a time sequence of players’ joint movements, based on which an unsupervised way is performed to extract the sub-sequences with high occurrence frequencies. These sub-sequences, called patterns, reflect the technical styles and tactics of the players, and offer an effective manner to organize the video. Evaluations on four hour broadcasting tennis videos show very promising results.
6086436
3D Line Image Analysis - A Heuristic Parallel Approach with Learning and Recognition
Abstract A heuristic parallel approach for (3d) line image analysis is introduced by using the concept of coordinated graph, layered graph representation, and parallel matching techniques and it significantly reduces the time required for dealing with three-dimensional line image analysis problems. Their fundamental properties and the concept of finite representations are investigated, and an interactive and iterative recognition algorithm with learning and recognition as a part of each other is presented. Several interested examples including curved and disconnected line images are illustrated. In addition to its importance in theoretical studies, this approach can also be applied to 3d object recognition, image processing, and computer vision in industrial, military, and medical fields.
45269182
Maximally flat allpass fractional Hilbert transformers
Recently, a generalization of the Hilbert transformer, the fractional Hilbert transformer, was defined and developed. In this paper, we propose a design of the allpass filter to realize the fractional Hilbert transformer based on the maximally flat approximation to the desired phase response. The coefficients are solved analytically for the traditional Hilbert transformer which is a special case of the fractional Hilbert transformer. Based on the closed-form coefficients, we show that the maximally flat allpass Hilbert transformers are stable. Design examples indicate that the proposed filters exhibit good approximation to the desired frequency response.
34131767
Problem Solving With Insufficient Resources
A new approach, "controlled concurrency," is introduced for inference control in an adaptive reasoning system working with insufficient knowledge and resources. With this method, a problem-solving process is constructed from atomic steps in run time, according to the system's past experience and the current context. The system carries out many such processes in parallel by distributing its resources among them, and dynamically adjusting the distribution according to feedback. A data structure, "bag," is designed to support this dynamic time-space allocation, and is a kind of probabilistic priority queue. This approach provides a flexible, efficient, and adaptive control mechanism for real-time systems working with uncertain knowledge. To analyze problem solving in such a system, the traditional computability theory and computational complexity theory become inappropriate, because the system no longer follows problem-specific algorithms in problem solving.