Stochastic Relational Processes and Models

نویسنده

  • Ingo Thon
چکیده

In order to solve real-world tasks, intelligent machines need to be able to act in noisy worlds where the number of objects and the number of relations among the objects varies from domain to domain. Algorithms that address this setting fall into the subfield of artificial intelligence known as statistical relational artificial intelligence (StaR-AI). While early artificial intelligence systems allowed for expressive relational representations and logical reasoning, they were unable to deal with uncertainty. On the other hand, traditional probabilistic reasoning and machine learning systems can capture the inherent uncertainty in the world, but employ a purely propositional representation and are unable to capture the rich, structured nature of many real-world domains. StaR-AI encompasses many strains of research within artificial intelligence. One such direction is statistical relational learning which wants to unify relational and statistical learning techniques. However, only a few of these techniques support decision making processes. This thesis advances the state-of-the-art in statistical relational learning by making three important contributions. The first contribution is the introduction of a novel representation, called causal probabilistic time-logic (CPT-L) for stochastic relational processes. These are stochastic processes defined over relational statespaces and they occupy an intermediate position in the expressiveness/efficiency trade-off. By focusing on the sequential aspect and deliberately avoiding the

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Application of Stochastic Optimal Control, Game Theory and Information Fusion for Cyber Defense Modelling

The present paper addresses an effective cyber defense model by applying information fusion based game theoretical approaches‎. ‎In the present paper, we are trying to improve previous models by applying stochastic optimal control and robust optimization techniques‎. ‎Jump processes are applied to model different and complex situations in cyber games‎. ‎Applying jump processes we propose some m...

متن کامل

An extension of stochastic differential models by using the Grunwald-Letnikov fractional derivative

Stochastic differential equations (SDEs) have been applied by engineers and economists because it can express the behavior of stochastic processes in compact expressions. In this paper, by using Grunwald-Letnikov fractional derivative, the stochastic differential model is improved. Two numerical examples are presented to show efficiency of the proposed model. A numerical optimization approach b...

متن کامل

Inference in Dynamic Probabilistic Relational Models

Stochastic processes that involve the creation and modification of objects and relations over time are widespread, but relatively poorly studied. For example, accurate fault diagnosis in factory assembly processes requires inferring the probabilities of erroneous assembly operations, but doing this efficiently and accurately is difficult. Modeled as dynamic Bayesian networks, these processes ha...

متن کامل

Modelling Reciprocating Relationships with Hawkes Processes

We present a Bayesian nonparametric model that discovers implicit social structure from interaction time-series data. Social groups are often formed implicitly, through actions among members of groups. Yet many models of social networks use explicitly declared relationships to infer social structure. We consider a particular class of Hawkes processes, a doubly stochastic point process, that is ...

متن کامل

Distributed Relational State Representations for Complex Stochastic Processes

Several promising variants of hidden Markov models (HMMs) have recently been developed to efficiently deal with large state and observation spaces and relational structure. Many application domains, however, have an apriori componential structure such as parts in musical scores. In this case, exact inference within relational HMMs still grows exponentially in the number of components. In this p...

متن کامل

A Comparative Analysis of Institutional Identities in a Corpus of English and Persian News Interviews

Institutional identity as a concept in CDA is a field of study that deals with the identities that individuals in institutions obtain, one that merits deep research attention. News interviews as institutional instances can be analyzed based on the impersonal structures because interviewees see themselves as part of the institution and they may not take responsibility when they encounter problem...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011