CPT-L: an Efficient Model for Relational Stochastic Processes

نویسندگان

  • Ingo Thon
  • Niels Landwehr
  • Luc De Raedt
چکیده

Agents that learn and act in real-world environments have to cope with both complex state descriptions and non-deterministic transition behavior of the world. Standard statistical relational learning techniques can capture this complexity, but are often inefficient. We present a simple probabilistic model for such environments based on CP-Logic. Efficiency is maintained by restriction to a fully observable setting and the use of efficient inference algorithms based on binary decision diagrams.

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

Stochastic Relational Processes and Models

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...

متن کامل

کاربرد مدل ارتباطی تحلیل پوششی داده‌های دو مرحله‌ای در ارزیابی کارایی

     The objective of this paper is to investigate, via relational model of two-stage data       envelopment analysis, the efficiency decomposition in a two-stage production process where the outputs of the first stage are the inputs of the second stage. Unlike previous studies which used to treat the whole production process and the two sub-processes as in-dependent, this paper takes the serie...

متن کامل

From Non-Deterministic to Probabilistic Planning with the help of Statistical Relational Learning

Using machine learning techniques for planning is getting increasingly more important in recent years. Various aspects of action models can be induced from data and then exploited for planning. For probabilistic planning, natural candidates are learning of action effects and their probabilities. For expressive formalisms such as PPDDL, this is a difficult problem since they can introduce easily...

متن کامل

A generalized super-efficiency model for ranking extreme efficient DMUs in stochastic DEA

In this current study a generalized super-efficiency model is first proposed for ranking extreme efficient decision making units (DMUs) in stochastic data envelopment analysis (DEA) and then, a deterministic (crisp) equivalent form of the stochastic generalized super-efficiency model is presented. It is shown that this deterministic model can be converted to a quadratic programming model. So fa...

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 2008