In normative political theory, it is widely accepted that democratic decision-making cannot be
reduced to voting alone, but that it requires reasoned and well-informed discussion by those …

When making decisions, people naturally face uncertainty about the potential consequences
of their actions due in part to limits in their capacity to represent, evaluate or deliberate …

Conditionalization is one of the central norms of Bayesian epistemology. But there are a
number of competing formulations, and a number of arguments that purport to establish it. In …

The concept of updating (or conditioning or revising) a probability distribution is fundamental
in (machine) learning and in predictive coding theory. The two main approaches for doing so …

Evidence in probabilistic reasoning may be'hard'or'soft', that is, it may be of yes/no form, or it
may involve a strength of belief, in the unit interval [0, 1]. Reasoning with soft,[0, 1]-valued …

How can individuals exchange information to learn from each other despite their privacy
needs and security concerns? For example, consider individuals deliberating a contentious …

A group is often construed as one agent with its own probabilistic beliefs (credences), which
are obtained by aggregating those of the individuals, for instance through averaging. In their …

Several philosophers have proposed Knowledge-Based Decision Theories (KDTs)—
theories that require agents to maximize expected utility as yielded by utility and probability …

Abstract Expectation Maximisation (EM) and Latent Dirichlet Allocation (LDA) are two
frequently used inference algorithms, for finding an appropriate mixture of latent variables …

When an agent learns of an expert's credence in a proposition about which they are an
expert, the agent should defer to the expert and adopt that credence as their own. This is a …