Causal reversibility blends and causality for concurrent systems. It indicates that an action can be undone provided all of its consequences have been already, thus making it possible to bring the system back a past consistent state. Time is instead considered in field stochastic processes, mostly efficient analysis purposes. A performance model based on continuous-time Markov chain time revers...

The process of managing inconsistency is a fundamental activity that permeates a large part of the systems development process. Failure to identify inconsistencies may lead to major problems in the operation of a system, while failure to support a range of inconsistency handling strategies can lead to a rigid and impractical development process. We argue, therefore, that the inconsistency manag...

Most approaches to causal discovery assume a fixed (or time-invariant) causal model; however, in practical situations, especially in neuroscience and economics, causal relations might be timedependent for various reasons. This paper aims to identify the time-dependent causal relations from observational data. We consider general formulations for time-varying causal modeling on stochastic proces...

We propose an unsupervised stream processing framework that learns a Bayesian representation of observed spatio-temporal activities and their causal relations. The dynamics of the activities are modeled using sparse Gaussian processes and their causal relations using a causal Bayesian graph. This allows the model to be efficient through compactness and sparsity in the causal graph, and to provi...

The dilemma of free will is that if actions are caused deterministically, then they are not free, and if they are not caused deterministically then they are not free either because then they happen by chance and are not up to the agent. I shall propose a conception of free will that solves this dilemma. It may seem to many metaphysically more extravagant than other conceptions but I shall sugge...

According to existing accounts of causation, people rely on a single criterion to identify the cause of an event. The phenomenon of causal illusions raises problems for such views. Causal illusions arise when a particular factor is perceived to be causal despite knowledge indicating otherwise. According to what we will call the Dual-Process Hypothesis of Causal Identification, identifying a cau...