Home Abstract Materials Speakers Contact

Knowledge-based Sequential Decision-Making under Uncertainty

AAAI 2019 Tutorial (MP5Q), Monday (1:30 - 3:15 PM), January 28, 2019

Hilton Hawaiian Village, Honolulu, Hawaii, USA

Tutorial Overview

Tutorial Abstract

In this tutorial, we will focus on work at the intersection of declarative representations and probabilistic representations for reasoning and learning. There is significant prior work in probabilistic sequential decision-making (SDM) and in declarative methods for knowledge representation and reasoning (KRR).

  • We will highlight the complementary capabilities of these methods, summarize existing research that combines these capabilities, and identify some open problems in the design and use of such integrated systems in different application domains.

  • We will focus on the interplay between goal-oriented SDM and declarative KRR, and demonstrate how this interplay provides novel opportunities for addressing the open problems in the individual research areas.

  • We will draw upon our own expertise in developing architectures that exploit these complementary capabilities for robots interacting and collaborating with each other and with humans.

Our goal is to encourage many more researchers to explore the integration of probabilistic SDM and declarative KRR methods in different application domains.

This tutorial will thus be of interest to researchers in these areas and in application domains such as robotics, computer vision, and natural language processing.

Official information on AAAI website.

1 / 3
Shiqi Zhang giving the talk
2 / 3
75+ registrants, the most popular quarter-day tutorial!
3 / 3
Some other concurrent tutorials


Tutorial materials will be added here.

  • Talk slides are available online.

  • Girl in a jacket

  • A survey paper (still preliminary) is available on arXiv

  • Girl in a jacket

Related Papers (incomplete, more to be added)


This tutorial will be co-offered by Shiqi Zhang, and Mohan Sridharan.

  • Shiqi Zhang is an Assistant Professor at the Department of Computer Science, the State University of New York (SUNY) at Binghamton. He was a Postdoctoral Fellow at the University of Texas at Austin (2014-2016), and received his Ph.D. in Computer Science (2013) from Texas Tech University.

  • Mohan Sridharan is a Senior Lecturer in the School of Computer Science at University of Birmingham (UK). He received his Ph.D. from The University of Texas at Austin (USA). His research interests include knowledge representation and reasoning, machine learning, computational vision, and cognitive systems, as applied to human-robot collaboration.

Contact Information

If you have any questions, comments, or suggestions. Please do not hesitate to contact (any one of) the speakers.
  • szhang@cs.binghamton.edu
  • m.sridharan@bham.ac.uk