A Default-Logic Paradigm for Legal Reasoning and Factfinding

Unlike research in linguistics and artificial intelligence, legal research has not used advances in logical theory very effectively. This article uses default logic to develop a paradigm for analyzing all aspects of legal reasoning, including factfinding. The article provides a formal model that integrates legal rules and policies with the evaluation of both expert and non-expert evidence – whether the reasoning occurs in courts or administrative agencies, and whether in domestic, foreign, or international legal systems. This paradigm can standardize the representation of legal reasoning, guide empirical research into the dynamics of such reasoning, and put the representations and research results to immediate use through artificial intelligence software. This new model therefore has the potential to transform legal practice and legal education, as well as legal theory

EEG source-space synchrostate transitions and Markov modeling in the math-gifted brain during a long-chain reasoning task

To reveal transition dynamics of global neuronal networks of math‐gifted adolescents in handling long‐chain reasoning, this study explores momentary phase‐synchronized patterns, that is, electroencephalogram (EEG) synchrostates, of intracerebral sources sustained in successive 50 ms time windows during a reasoning task and non‐task idle process. Through agglomerative hierarchical clustering for functional connectivity graphs and nested iterative cosine similarity tests, this study identifies seven general and one reasoning‐specific prototypical functional connectivity patterns from all synchrostates. Markov modeling is performed for the time‐sequential synchrostates of each trial to characterize the interstate transitions. The analysis reveals that default mode network, central executive network (CEN), dorsal attention network, cingulo‐opercular network, left/right ventral frontoparietal network, and ventral visual network aperiodically recur over non‐task or reasoning process, exhibiting high predictability in interactively reachable transitions. Compared to non‐gifted subjects, math‐gifted adolescents show higher fractional occupancy and mean duration in CEN and reasoning‐triggered transient right frontotemporal network (rFTN) in the time course of the reasoning process. Statistical modeling of Markov chains reveals that there are more self‐loops in CEN and rFTN of the math‐gifted brain, suggesting robust state durability in temporally maintaining the topological structures. Besides, math‐gifted subjects show higher probabilities in switching from the other types of synchrostates to CEN and rFTN, which represents more adaptive reconfiguration of connectivity pattern in the large‐scale cortical network for focused task‐related information processing, which underlies superior executive functions in controlling goal‐directed persistence and high predictability of implementing imagination and creative thinking during long‐chain reasoning

Effects of Economic Interactions on Credit Risk

We study a credit risk model which captures effects of economic interactions on a firm's default probability. Economic interactions are represented as a functionally defined graph, and the existence of both cooperative, and competitive, business relations is taken into account. We provide an analytic solution of the model in a limit where the number of business relations of each company is large, but the overall fraction of the economy with which a given company interacts may be small. While the effects of economic interactions are relatively weak in typical (most probable) scenarios, they are pronounced in situations of economic stress, and thus lead to a substantial fattening of the tails of loss distributions in large loan portfolios. This manifests itself in a pronounced enhancement of the Value at Risk computed for interacting economies in comparison with their non-interacting counterparts.Comment: 24 pages, 6 figure

Adaptive logic characterizations of input/output logic

We translate unconstrained and constrained input/output logics as introduced by Makinson and van der Torre to modal logics, using adaptive logics for the constrained case. The resulting reformulation has some additional benefits. First, we obtain a proof-theoretic (dynamic) characterization of input/output logics. Second, we demonstrate that our framework naturally gives rise to useful variants and allows to express important notions that go beyond the expressive means of input/output logics, such as violations and sanctions

Mental states in communication

Abstract. This paper is concerned with the mental processes involved in intentional communication. I describe an agent's cognitive architecture as the set of cognitive dynamics (i.e., sequences of mental states with contents) she may entertain. I then describe intentional communication as one such specific dynamics, arguing against the prevailing view that communication consists in playing a role in a socially shared script. The cognitive capabilities needed for such dynamics are midreading (i.e., the ability to reason upon another individual's mental states), and communicative planning (i.e., the ability to dynamically represent and act in a communicative situation)