Reasoning and Learning in Real-World Systems for Long-Term Autonomy
(LTA 2018)

AAAI 2018 Fall Symposium

October 18-19, 2018

Arlington, VA, U.S.A.


  • November 2018 - The proceedings are now published and the papers are linked below.
  • October 2018 - The symposium was held in Arlington, VA!
  • October 2018 - Maarten Sierhuis has joined as an invited speaker!
  • September 2018 - The schedule has been posted below.
  • August 2018 - Papers have been accepted: 12 long and 6 short!
  • July 2018 - Invited speakers include Nick Hawes, Tom Wagner, and Peter Wurman!
  • July 2018 - Nissan Research Center Silicon Valley is sponsoring the symposium!
  • June 2018 - Program committee has been formed.
  • May 2018 - The LTA 2018 website has been launched.


Over the past decade, decision-making agents have been increasingly deployed in industrial settings, consumer products, healthcare, education, and entertainment. The development of drone delivery services, virtual assistants, and autonomous vehicles have highlighted numerous challenges surrounding the operation of autonomous systems in unstructured environments. This includes mechanisms to support autonomous operations over extended periods of time, techniques that facilitate the use of human assistance in learning and decision-making, learning to reduce the reliance on humans over time, addressing the practical scalability of existing methods, relaxing unrealistic assumptions, and alleviating safety concerns about deploying these systems.

This symposium aims to identify the challenges and bridge the gaps between theoretical frameworks for planning and learning in autonomous agents and the requirements imposed by deployment in the real world. Our goal is to help identify research avenues that can move the AI community beyond highly theoretical results for simple domains or highly engineered one-shot solutions for realistic applications. We seek papers that find a common middle ground between theory and applications, and analyze the lessons learned from these efforts, particularly with respect to long-term autonomy.

The symposium combines invited talks, presentations, and discussions from both an AI and a robotics perspective.


Topics of interest include, but are not limited to, the following:

  • Decision-making representations, models, and algorithms for the real world
  • Hierarchical and multi-objective solutions for scalable planning and learning
  • Efficient integrations of task and motion planning
  • Integrating planning, reasoning, and learning for long-term deployments
  • Safety in real-world decision-making and learning
  • Scalable multiagent and human-in-the-loop techniques
  • Proactively incorporating human feedback in decision-making
  • Leveraging the complimentary capabilities of humans and robots in real-world tasks
  • Evaluation metrics for long-term autonomy
  • Case studies and descriptions of deployed autonomous systems
  • Lessons learned from deployed applications of autonomous systems

Important Dates

Paper Submission Deadline:
Tuesday, July 31, 2018
Notification of Acceptance:
Tuesday, August 14, 2018
Camera-Ready Submission:
Friday, September 14, 2018
Symposium Date:
Thursday, October 18, 2018 to
Friday, October 19, 2018

Invited Talks

Nick Hawes Speaker: Dr. Nick Hawes, Associate Professor of Robotics at the University of Oxford
Title: Learning From Four Years of Mobile Autonomy
Abstract: In this talk I will look back over four years of long-term deployments of autonomous mobile robots in everyday environments. From this I will present examples of the kinds of things that mobile robots can learn over long autonomous operations in such environments, including navigation information, human activities, object models, and mission schedules. Following this I will explore the issues (software, hardware, and social) that impacted upon the autonomy of our deployed robots, and look at what we can learn from these experiences as both AI practitioners and as engineers deploying robots in real environments.

Maarten Sierhuis Speaker: Dr. Maarten Sierhuis, Chief Technology Director at Nissan Research Center - Silicon Valley, Founder of Ejenta
Title: Seamless Autonomous Mobility (SAM)
Abstract: "Advances in artificial intelligence are making vehicles smarter, more responsive, and better at making decisions in a variety of driving environments. But we are still not at a point where autonomous vehicles can know exactly how to handle unpredictable situations. This is one of the roadblocks to realizing a fully autonomous future for driving. The solution is Nissan’s Seamless Autonomous Mobility system or SAM." See more here.

Peter Wurman Speaker: Dr. Peter Wurman, VP of Engineering at Cogitai, Former Co-founder of Kiva Systems
Title: The Disruptive Power of Robots
Abstract: Kiva Systems introduced swarms of agile robots into an industry dominated by stationary conveyor systems. The path from concept through successful startup and eventual acquisition involved challenges on all fronts. In this talk I’ll explain the business problem that motivated the innovation, Kiva technology and the benefits it brought to customers, and the future of applications of robotics in warehouses.

Accepted Papers

Session #1 - Planning - Session Chair: Kyle Wray

  • A Practical Distributed Knowledge-Based Reasoning and Decision-Theoretic Planning for Multi-robot Service Systems
    Abdel-Illah Mouaddib and Laurent Jeanpierre
    [bib] [pdf]

  • Risk-Aware Planning by Extracting Uncertainty from Deep Learning-Based Perception
    Maymoonah Toubeh and Pratap Tokekar
    [bib] [pdf]

  • Towards Perception Aware Task-Motion Planning
    Antony Thomas, Sunny Amatya, Fulvio Mastrogiovanni, and Marco Baglietto
    [bib] [pdf]

  • From Abstract to Executable Models for Multi-Agent Path Finding on Real Robots [Short Presentation]
    Roman Barták, Jiří Švancara, Věra Škopková, and David Nohejl
    [bib] [pdf]

Session #2 - Architectures and Models - Session Chair: Abdel-Illah Mouaddib

  • SOMA: A Framework for Understanding Change in Everyday Environments Using Semantic Object Maps
    Lars Kunze, Hakan Karaoguz, Jay Young, Ferdian Jovan, John Folkesson, Patric Jensfelt, and Nick Hawes
    [bib] [pdf]

  • SocialAnnotator: Annotator Selection Using Activity and Social Context
    H. M. Sajjad Hossain and Nirmalya Roy
    [bib] [pdf]

  • Policy Networks for Reasoning in Long-Term Autonomy
    Kyle Hollins Wray and Shlomo Zilberstein
    [bib] [pdf]

  • LAAIR: A Layered Architecture for Autonomous Interactive Robots
    Yuqian Jiang, Nick Walker, Minkyu Kim, Nicolas Brissonneau, Daniel S. Brown, Justin W. Hart, Scott Niekum, Luis Sentis, and Peter Stone
    [bib] [pdf]

  • Using hierarchical expectations grounded in perception for failure reasoning during task execution [Short Presentation]
    Priyam Parashar, Henrik I. Christensen, and Ashok K. Goel
    [bib] [pdf]

Session #3 - Reinforcement Learning - Session Chair: Roman Barták

  • Partial Policy Re-use in Connected Health Systems
    Matthew Saponaro and Keith Decker
    [bib] [pdf]

  • Predictions, Surprise, and Predictions of Surprise in General Value Function Architectures
    Johannes Günther, Alex Kearney, Michael R. Dawson, Craig Sherstan, and Patrick M. Pilarski
    [bib] [pdf]

  • Multi-Fidelity Model-Free Reinforcement Learning with Gaussian Processes
    Varun Suryan, Nahush Gondhalekar, and Pratap Tokekar
    [bib] [pdf]

  • Evaluating Predictive Knowledge [Short Presentation]
    Alex Kearney, Anna Koop, Craig Sherstan, Johannes Günther, Richard Sutton, Patrick Pilarski, and Matthew Taylor
    [bib] [pdf]

Session #4 - Real-World Systems - Session Chair: David Kortenkamp

  • Learning and Generalisation of Primitives Skills Towards Robust Dual-arm Manipulation
    Èric Pairet, Paola Ardón, Frank Broz, Michael Mistry, and Yvan Petillot
    [bib] [pdf]

  • Towards Robust Grasps: Using the Environment Semantics for Robotic Object Affordances
    Paola Ardón, Èric Pairet, Subramanian Ramamoorthy, and Katrin Solveig Lohan
    [bib] [pdf]

  • Behavior Modeling for Autonomous Driving
    Aniket Bera and Dinesh Manocha
    [bib] [pdf]

  • Deep CNN and Probabilistic DL Reasoning for Contextual Affordances
    Hazem Abdelkawy, Sandro Rama Fiorini, Abdelghani Chibani, Naouel Ayari, and Yacine Amirat
    [bib] [pdf]

  • Big Data and Deep Learning Models for Automatic Dependent Surveillance Broadcast (ADS-B) [Short Presentation]
    Ying Zhao, Richard Wu, Matthew Xi, Andrew Polk, and Tony Kendall
    [bib] [pdf]

Paper Presentations

Papers will be presented either in a long presentation format (25 minute) or short presentation format (15 minute) based on paper length and relevance to long-term autonomy (LTA).

To focus the discussion on the symposium's topic, all presentations should reserve 3-5 minutes at the end of their talk to relate their paper directly to long-term autonomy. They can provide their brief perspectives on the topic if appropriate as well. The idea is to complete the talk by taking a step back and examining: (1) how the work falls within the broader scope of long-term autonomy, and (2) any other problems, solutions, challenges, applications, questions, etc. outside the current work might be interesting to the research community working on long-term autonomy.

Thus, long presentations should follow the structure: 15 minutes of paper content, then 5 minutes of relations to LTA, and then 5 minutes of Q&A. Short presentations should follow the structure: 10 minutes of paper content, then 3 minutes of relations to LTA, and then 2 minutes of Q&A.

Panel Discussion

The panel discussion will conclude the symposium with reflections and perspectives from the invite talks and papers on the state of long-term autonomy overall.

Moderator: Joydeep Biswas, University of Massachusetts Amherst

The panel members will include the invited speakers.

Tentative Program Schedule

Thursday, October 18

8:50 am - 9:00 am Welcome
9:00 am - 10:30 am Session #1 - Planning (3 Long, 1 Short)
10:30 am - 11:00 am Coffee Break
11:00 am - 12:00 pm Invited Talk #1 - Dr. Nick Hawes
12:00 pm - 1:30 pm Lunch Break
1:30 pm - 3:30 pm Session #2 - Architectures and Models (4 Long, 1 Short)
3:30 pm - 4:00 pm Coffee Break
4:00 pm - 5:00 pm Invited Talk #2 - Dr. Maarten Sierhuis
6:00 pm - 7:00 pm AAAI Symposia Reception

Friday, October 19

9:00 am - 10:30 am Session #3 - Reinforcement Learning (3 Long, 1 Short)
10:30 am - 11:00 am Coffee Break
11:00 am - 12:00 pm Invited Talk #3 - Dr. Peter Wurman
12:00 pm - 1:30 pm Lunch Break
1:30 pm - 3:30 pm Session #4 - Real-World Systems (4 Long, 1 Short)
3:30 pm - 4:00 pm Coffee Break
4:00 pm - 5:00 pm Panel Discussion
6:00 pm - 7:00 pm AAAI Plenary Session

Saturday, October 20

This symposium will not hold anything on the final half-day.



Program Committee:


Please direct questions regarding the symposium to "longtermautonomy2018 'at'".