Social network data is generally incomplete with missing information about nodes and their interactions. Here we propose a spatialtemporal latent point process model that describes geographically distributed interactions between pairs of entities. In contrast to most existing approaches, we assume that interactions are not fully observable, and certain interaction events lack information about ...

This paper describes a method to represent temporal lo-calization in such a way that it could be used in a system for natural language processing. We show that linguistic information is not suucient to deal with temporal lo-calization adverbials in natural language processing. A representation of time with a greater level of abstraction must be used. We propose an implementation of such a repre...

Markov Decision Processes (MDPs), currently a popular method for modeling and solving decision theoretic planning problems, are limited by the Markovian assumption: rewards and dynamics depend on the current state only, and not on previous history. Non-Markovian decision processes (NMDPs) can also be defined, but then the more tractable solution techniques developed for MDP’s cannot be directly...

Recordings from single cells in human medial temporal cortex confirm that sensory processing forms explicit neural representations of the objects and concepts needed for a causal model of the world.

The mismatch negativity (MMN) is a frontal negative deflection in the human event-related potential that typically occurs when a repeating auditory stimulus changes in some manner. The MMN can be elicited by many kinds of stimulus change, varying from simple changes in a single stimulus feature to abstract changes in the relationship between stimuli. The main intracerebral sources for the MMN a...

Previous studies have reported greater activity in the parahippocampal cortex during true memory than false memory, which has been interpreted as reflecting greater sensory processing during true memory. However, in these studies, sensory detail and contextual information were confounded. In the present fMRI study, we employed a novel paradigm to dissociate these factors. During encoding, abstr...

In the study of dynamical processes on networks, there has been intense focus on network structure—i.e., the arrangement of edges and their associated weights—but the effects of the temporal patterns of edges remains poorly understood. In this chapter, we develop a mathematical framework for random walks on temporal networks using an approach that provides a compromise between abstract but unre...

The language features and formal definitions of the three most popular process algebras, csp, ccs and lotos, are introduced and compared.

We propose algorithms for agents in Markov Decision Processes that plan to maximally satisfy multiple, potentially conflicting, temporal logic goals. These agents (1) satisfy as many goals as possible; (2) prioritize more important goals; and (3) violate goals, if necessary, for the minimum possible duration. We demonstrate the behaviors of such agents in two simple domains.