Distributed belief revision as applied within a descriptive model of jury deliberations

Belief revision is a well-research topic within AI. We argue that the new model of distributed belief revision as discussed here is suitable for general modelling of judicial decision making, along with extant approach as known from jury research. The new approach to belief revision is of general interest, whenever attitudes to information are to be simulated within a multi-agent environment with agents holding local beliefs yet by interaction with, and influencing, other agents who are deliberating collectively. In the approach proposed, it's the entire group of agents, not an external supervisor, who integrate the different opinions. This is achieved through an election mechanism, The principle of "priority to the incoming information" as known from AI models of belief revision are problematic, when applied to factfinding by a jury. The present approach incorporates a computable model for local belief revision, such that a principle of recoverability is adopted. By this principle, any previously held belief must belong to the current cognitive state if consistent with it. For the purposes of jury simulation such a model calls for refinement. Yet we claim, it constitutes a valid basis for an open system where other AI functionalities (or outer stiumuli) could attempt to handle other aspects of the deliberation which are more specifi to legal narrative, to argumentation in court, and then to the debate among the jurors.

Belief revision as applied within a descriptive model of jury deliberations

Belief revision is a well-researched topic within Artificial Intelligence (AI). We argue that the new model of belief revision as discussed here is suitable for general modelling of judicial decision making, along with the extant approach as known from jury research. The new approach to belief revision is of general interest, whenever attitudes to information are to be simulated within a multi-agent environment with agents holding local beliefs yet by interacting with, and influencing, other agents who are deliberating collectively. The principle of 'priority to the incoming information', as known from AI models of belief revision, is problematic when applied to factfinding by a jury. The present approach incorporates a computable model for local belief revision, such that a principle of recoverability is adopted. By this principle, any previously held belief must belong to the current cognitive state if consistent with it. For the purposes of jury simulation such a model calls for refinement. Yet, we claim, it constitutes a valid basis for an open system where other AI functionalities (or outer stimuli) could attempt to handle other aspects of the deliberation which are more specific to legal narratives, to argumentation in court, and then to the debate among the jurors.

Obtaining data to validate a model of an induction skull melting furnace

A casting route is often the most cost-effective means of producing engineering components. However, certain materials, particularly those based on Ti, TiAl and Zr alloy systems, are very reactive in the molten condition and must be melted in special furnaces. Induction Skull Melting (ISM) is the most widely-used process for melting these alloys prior to casting components such as turbine blades, engine valves, turbocharger rotors and medical prostheses. A major research project is underway with the specific target of developing robust techniques for casting TiAl components. The aims include increasing the superheat in the molten metal to allow thin section components to be cast, improving the quality of the cast components and increasing the energy efficiency of the process. As part of this, the University of Greenwich (UK) is developing a computer model of the ISM process in close collaboration with the University of Birmingham (UK) where extensive melting trials are being undertaken. This paper describes the experimental measurements to obtain data to feed into and to validate the model. These include measurements of the true RMS current applied to the induction coil, the heat transfer from the molten metal to the crucible cooling water, and the shape of the column of semi-levitated molten metal. Data are presented for Al, Ni and TiAl.

A computational model of coupled heat and moisture transfer with phase change in granular sugar during varying environmental conditions

As part of a comprehensive effort to predict the development of caking in granular materials, a mathematical model is introduced to model simultaneous heat and moisture transfer with phase change in porous media when undergoing temperature oscillations/cycling. The resulting model partial differential equations were solved using finite-volume procedures in the context of the PHYSICA framework and then applied to the analysis of sugar in storage. The influence of temperature on absorption/desorption and diffusion coefficients is coupled into the transport equations. The temperature profile, the depth of penetration of the temperature oscillation into the bulk solid, and the solids moisture content distribution were first calculated, and these proved to be in good agreement with experimental data. Then, the influence of temperature oscillation on absolute humidity, moisture concentration, and moisture migration for different parameters and boundary conditions was examined. As expected, the results show that moisture near boundary regions responds faster than farther away from them with surface temperature changes. The moisture absorption and desorption in materials occurs mainly near boundary regions (where interactions with the environment are more pronounced). Small amounts of solids moisture content, driven by both temperature and vapour concentration gradients, migrate between boundary and center with oscillating temperature.

Extended model of pedestrian escalator behaviour based on data collected within a Chinese underground station

This paper presents data relating to pedestrian escalator behaviour collected in an underground station in Shanghai, China. While data was not collected under emergency or simulated emergency conditions, it is argued that the data collected under rush-hour conditions - where commuters are under time pressures to get to work on time - may be used to approximate emergency evacuation conditions - where commuters are also under time pressures to exit the building as quickly as possible. Data pertaining to escalator/stair choice, proportion of walkers to riders, walker speeds and side usage are presented. The collected data is used to refine the buildingEXODUS escalator model allowing the agents to select whether to use an escalator or neighbouring parallel stair based on congestion conditiions at the base of the stair/escalator and expected travel times. The new model, together with the collected data, is used to simulate a series of hypothetical evacuation scenarios to demonstrate the impact of escalators on evacuation performance.

A unified 3D model of the VAR process

A 3D time-dependent model of the VAR process has been developed using CFD techniques. The model solves the coupled field equations for fluid flow, heat transfer (including phase change) and electromagnetic field, for both the electrode and the ingot. The motion of the electic arc 'preferred spot' can be specified based on observations. Correlations are sought between the local gap height, resulting from instantaneous liquid pool surface shape and electrode tip shape, and the arc motion. The detailed behaviour of the melting film on the electrode tip is studies using a spectral free surface technique, which allows investigation of the drops' detachment and drip shorts.

The eLIDA CAMEL nomadic model of collaborative partnership for a community of practice in design for learning

A nomadic collaborative partnership model for a community of practice (CoP) in Design for Learning (D4L) can facilitate successful innovation and continuing appraisals of effective professional practice, stimulated by a 'critical friend' assigned to the project. This paper reports on e-learning case studies collected by the JISC-funded UK eLIDA CAMEL Design for Learning Project. The project implemented and evaluated learning design (LD) tools in higher and further education within the JISC Design for Learning pedagogic programme (2006-07). Project partners trialled professional user evaluations of innovative e-learning tools with learning design function, collecting D4L case studies and LD sequences in post-16/HE contexts using LAMS and Moodle. The project brought together learning activity sequences within a collaborative e-learning community of practice based on the CAMEL (Collaborative Approaches to the Management of e-Learning) model, contributing to international D4L developments. This paper provides an overview of project outputs in e-learning innovations, including evaluations from teachers and students. The paper explores intentionality in the development of a CoP in design for learning, reporting on trials of LD and social software that bridged tensions between formalised intra-institutional e-learning relationships and inter-institutional professional project team dynamic D4L practitioner interactions. Following a brief report of D4L case studies and feedback, the catalytic role of the 'critical friend' is highlighted and recommended as a key ingredient in the successful development of a nomadic model of communities of practice for managing professional e-learning projects. eLIDA CAMEL Partners included the Association of Learning Technology (ALT), JISC infoNet, three universities and five FE/Sixth Form Colleges. Results reported to JISC demonstrated D4L e-learning innovations by practitioners, illuminated by the role of the 'critical friend'. The project also benefited from formal case study evaluations and the leading work of ALT and JISC infoNet in the development of the CAMEL model.