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.

Vibrational spectroscopy and DFT calculations of the di-amino acid peptide L-aspartyl-L-glutamic acid in the zwitterionic state

Solid state IR and Raman as well as aqueous solution state Raman spectra are reported for the linear di-amino acid peptide L-aspartyl-L-glutamic acid (L-Asp-L-Glu); the solution state Raman spectrum has also been obtained for the N,O-deuterated derivative. SCF-DFT calculations at the B3-LYP/cc-pVDZ level established that the structure and vibrational spectra of L-Asp-L-Glu can be interpreted using a model of the peptide with ten hydrogen-bonded water molecules, in conjunction with the conductor-like polarizable continuum solvation method. The DFT calculations resulted in the computation of a stable zwitterionic structure, which displays trans-amide conformation. The vibrational spectra were computed at the optimised molecular geometry, enabling normal coordinate analysis, which yielded satisfactory agreement with the experimental IR and Raman data. Computed potential energy distributions of the normal modes provided detailed vibrational assignments.

Vibrational spectra of α-amino acids in the zwitterionic state in aqueous solution and the solid state: DFT calculations and the influence of hydrogen bonding

The zwitterionic forms of the two simplest alpha-amino acids, glycine and l-alanine, in aqueous solution and the solid state have been modeled by DFT calculations. Calculations of the structures in the solid state, using PW91 or PBE functionals, are in good agreement with the reported crystal structures, and the vibrational spectra computed at the optimized geometries provide a good fit to the observed IR and Raman spectra in the solid state. DFT calculations of the structures and vibrational spectra of the zwitterions in aqueous solution at the B3-LYP/cc-pVDZ level were found to require both explicit and implicit solvation models. Explicit solvation was modeled by inclusion of five hydrogen-bonded water molecules attached to each of the five possible hydrogen-bonding sites in the zwitterion and the integration equation formalism polarizable continuum model (IEF-PCM) was employed, providing a satisfactory fit to observed IR and Raman spectra. Band assignments are reported in terms of potential-energy distributions, which differ in some respects to those previously reported for glycine and l-alanine.

Communication system model for information rate evaluation of differential detection over time-varying channels

A communication system model for mutual information performance analysis of multiple-symbol differential M-phase shift keying over time-correlated, time-varying flat-fading communication channels is developed. This model is a finite-state Markov (FSM) equivalent channel representing the cascade of the differential encoder, FSM channel model and differential decoder. A state-space approach is used to model channel phase time correlations. The equivalent model falls in a class that facilitates the use of the forward backward algorithm, enabling the important information theoretic results to be evaluated. Using such a model, one is able to calculate mutual information for differential detection over time-varying fading channels with an essentially finite time set of correlations, including the Clarke fading channel. Using the equivalent channel, it is proved and corroborated by simulations that multiple-symbol differential detection preserves the channel information capacity when the observation interval approaches infinity.