Predicting the metabolic energy costs of bipedalism using evolutionary robotics

To understand the evolution of bipedalism among the homnoids in an ecological context we need to be able to estimate theenerrgetic cost of locomotion in fossil forms. Ideally such an estimate would be based entirely on morphology since, except for the rare instances where footprints are preserved, this is hte only primary source of evidence available. In this paper we use evolutionary robotics techniques (genetic algoritms, pattern generators and mechanical modeling) to produce a biomimentic simulation of bipedalism based on human body dimensions. The mechnaical simulation is a seven-segment, two-dimensional model with motive force provided by tension generators representing the major muscle groups acting around the lower-limb joints. Metabolic energy costs are calculated from the muscel model, and bipedal gait is generated using a finite-state pattern generator whose parameters are produced using a genetic algorithm with locomotor economy (maximum distance for a fixed energy cost) as the fitness criterion. The model is validated by comparing the values it generates with those for modern humans. The result (maximum efficiency of 200 J m-1) is within 15% of the experimentally derived value, which is very encouraging and suggests that this is a useful analytic technique for investigating the locomotor behaviour of fossil forms. Initial work suggests that in the future this technique could be used to estimate other locomotor parameters such as top speed. In addition, the animations produced by this technique are qualitatively very convincing, which suggests that this may also be a useful technique for visualizing bipedal locomotion.

Violent Dissent and Rebellion in Africa

This article analyzes how the selection process for the executive affects the risk of rebellion and insurgencies in sub-Saharan Africa between 1971 and 1995. Four executive recruitment processes are distinguished, which are characteristic for the African context: (1) a process without elections, (2) single candidate elections, (3) single party, multiple candidate elections, and (4) multiparty executive elections. The results suggest that single candidate elections and multiparty elections substantially reduce the risk of insurgencies compared to systems without any kind of executive elections. They further show that during times of political instability the risk of large-scale violent dissent increases substantially. The article supports findings of the civil war literature that higher levels of income are associated with a lower risk of intrastate violence, while oil-exporting countries are at a higher risk of rebellion. In short, this article further strengthens the need to use more specific measures of elements of political regimes, which also take into account regional particularities, in order to paint a more informative picture of how political structures influence the risk of internal violence.

Strategic Alert Throttling for Intrusion Detection Systems

Network intrusion detection systems are themselves becoming targets of attackers. Alert flood attacks may be used to conceal malicious activity by hiding it among a deluge of false alerts sent by the attacker. Although these types of attacks are very hard to stop completely, our aim is to present techniques that improve alert throughput and capacity to such an extent that the resources required to successfully mount the attack become prohibitive. The key idea presented is to combine a token bucket filter with a realtime correlation algorithm. The proposed algorithm throttles alert output from the IDS when an attack is detected. The attack graph used in the correlation algorithm is used to make sure that alerts crucial to forming strategies are not discarded by throttling.

Imagine the Possibilities: Information without Overload

Information is often modelled as a set of relevant possibilities, treated as logically possible worlds. However, this has the unintuitive consequence that the logical consequences of an agent's information cannot be informative for that agent. There are many scenarios in which such consequences are clearly informative for the agent in question. Attempts to weaken the logic underlying each possible world are misguided. Instead, I provide a genuinely psychological notion of epistemic possibility and show how it can be captured in a formal model, which I call a fan. I then show how to use fans to build formal models of being informed, as well as knowledge, belief and information update.

Spatio-temporal filtering properties of a dendritic cable with active spines: a modeling study in the spike-diffuse-spike framework

The spike-diffuse-spike (SDS) model describes a passive dendritic tree with active dendritic spines. Spine-head dynamics is modeled with a simple integrate-and-fire process, whilst communication between spines is mediated by the cable equation. In this paper we develop a computational framework that allows the study of multiple spiking events in a network of such spines embedded on a simple one-dimensional cable. In the first instance this system is shown to support saltatory waves with the same qualitative features as those observed in a model with Hodgkin-Huxley kinetics in the spine-head. Moreover, there is excellent agreement with the analytically calculated speed for a solitary saltatory pulse. Upon driving the system with time varying external input we find that the distribution of spines can play a crucial role in determining spatio-temporal filtering properties. In particular, the SDS model in response to periodic pulse train shows a positive correlation between spine density and low-pass temporal filtering that is consistent with the experimental results of Rose and Fortune [1999, Mechanisms for generating temporal filters in the electrosensory system. The Journal of Experimental Biology 202, 1281-1289]. Further, we demonstrate the robustness of observed wave properties to natural sources of noise that arise both in the cable and the spine-head, and highlight the possibility of purely noise induced waves and coherent oscillations.

Laying out the future of final-form digital documents

It is just over 20 years since Adobe's PostScript opened a new era in digital documents. PostScript allows most details of rendering to be hidden within the imaging device itself, while providing a rich set of primitives enabling document engineers to think of final-form rendering as being just a sophisticated exercise in computer graphics. The refinement of the PostScript model into PDF has been amazingly successful in creating a near-universal interchange format for complex and graphically rich digital documents but the PDF format itself is neither easy to create nor to amend. In the meantime a whole new world of digital documents has sprung up centred around XML-based technologies. The most widespread example is XHTML (with optional CSS styling) but more recently we have seen Scalable Vector Graphics (SVG) emerge as an XML-based, low-level, rendering language with PostScript-compatible rendering semantics. This paper surveys graphically-rich final-form rendering technologies and asks how flexible they can be in allowing adjustments to be made to final appearance without the need for regenerating a whole page or an entire document. Particular attention is focused on the relative merits of SVG and PDF in this regard and on the desirability, in any document layout language, of being able to manipulate the graphic properties of document components parametrically, and at a level of granularity smaller than an entire page.

Artificial Immune Tissue using Self-Organizing Networks

As introduced by Bentley et al. (2005), artificial immune systems (AIS) are lacking tissue, which is present in one form or another in all living multi-cellular organisms. Some have argued that this concept in the context of AIS brings little novelty to the already saturated field of the immune inspired computational research. This article aims to show that such a component of an AIS has the potential to bring an advantage to a data processing algorithm in terms of data pre-processing, clustering and extraction of features desired by the immune inspired system. The proposed tissue algorithm is based on self-organizing networks, such as self-organizing maps (SOM) developed by Kohonen (1996) and an analogy of the so called Toll-Like Receptors (TLR) affecting the activation function of the clusters developed by the SOM.

Simulation Optimization of the Crossdock Door Assignmnet Problem

The purpose of this report is to present the Crossdock Door Assignment Problem, which involves assigning destinations to outbound dock doors of Crossdock centres such that travel distance by material handling equipment is minimized. We propose a two fold solution; simulation and optimization of the simulation model - simulation optimization. The novel aspect of our solution approach is that we intend to use simulation to derive a more realistic objective function and use Memetic algorithms to find an optimal solution. The main advantage of using Memetic algorithms is that it combines a local search with Genetic Algorithms. The Crossdock Door Assignment Problem is a new domain application to Memetic Algorithms and it is yet unknown how it will perform.

Sensing Danger: Innate Immunology for Intrusion Detection

The immune system provides an ideal metaphor for anomaly detection in general and computer security in particular. Based on this idea, artificial immune systems have been used for a number of years for intrusion detection, unfortunately so far with little success. However, these previous systems were largely based on immunological theory from the 1970s and 1980s and over the last decade our understanding of immunological processes has vastly improved. In this paper we present two new immune inspired algorithms based on the latest immunological discoveries, such as the behaviour of Dendritic Cells. The resultant algorithms are applied to real world intrusion problems and show encouraging results. Overall, we believe there is a bright future for these next generation artificial immune algorithms

Open Access Repositories & Scholarly Publication

This presentation briefly covers some of the issues around Open Access as it pertains to institutional repositories in the UK higher educational sector. It includes an overview of the current activities of SHERPA, along with the benefits, concerns and potential resolutions of issues in the open access sector. Some speculation as to future trends and developments in scholarly publishing and open access is included. The presentation is in no way comprehensive, and is intended to give an overview of the subject to a general audience who will be engaged with academic and scholarly publishing on a variety of levels.

Belief and Bounded Rationality

Predictive accounts of belief ascription, either following the principle of charity or Dennett's intentional stance, have proved popular recently. However, such accounts require us first to treat agents as perfectly rational agents and then revise this assumption as appropriate. I argue that such downwards revision is no easy task and that several proposed accounts are not satisfactory. I propose a way of characterising agent's belief states which shares Dennett's approach but avoids treating agents as perfectly rational, and develop a formal account in terms of fan models.

Rule-based and Resource-bounded: A New Look at Epistemic Logic

Syntactic logics do not suffer from the problems of logical omniscience but are often thought to lack interesting properties relating to epistemic notions. By focusing on the case of rule-based agents, I develop a framework for modelling resource-bounded agents and show that the resulting models have a number of interesting properties.