The International Summer School on Planning and Scheduling will be held in conjunction with ICAPS 2018. The summer school provides an educational program for graduate students and young researchers. The program will focus on a selection of topics that are relevant for both theory and practice, covering approaches and topcis around a thread of planning under uncertainty: modeling, classic and sample-based planning algorithms (such as Monte Carlo Tree Search), reinforcement learning, model-based algorithms, and applications.

General information

Chairs: Alan Fern, Joerg Hoffmann, Michael Kaisers
Date: June 20 – 23, 2018
Location: Noordwijk, The Netherlands
Venue: De Baak Seaside
Accommodation: The summer school has reserved accommodation for participants, which can be booked as part of the registration process.

Important dates

March 23, 2018
Application and grant request
March 30, 2018
Notification of admission
May 11, 2018
Notification of grant allocation
May 18, 2018
Payment of registration fees
June 20 – 23, 2018
Summer school

School Program and Speakers

The summer school will start around 9am on Wednesday 20 June, and lasts until around 5pm on Saturday 23 June. The program of the school is under construction, and further information will be posted here as it becomes available.

Confirmed lecturers at the school

  • Iadine Chades,
  • Zico Kolter,
  • Malte Helmert: Malte Helmert is an Associate Professor of Computer Science at the University of Basel. His main research interests are in classical planning and heuristic search, with an emphasis on domain-independent algorithms for synthesizing distance heuristics in factored state spaces. His research group at the University of Basel leads the development of the Fast Downward planning system.
  • Thomas Keller: Thomas Keller is a research associate at the AI group of the University of Basel. He received his PhD from the University of Freiburg (Germany) in July 2015. His main research interests are in probabilistic planning with a focus on Monte-Carlo Tree Search methods and Heuristic Search. Thomas received the ICAPS 2017 Best Dissertation Award and is the main developer of the Prost planning system that won IPPC 2011 and 2014.
  • Mausam: Mausam is an Associate Professor of Computer Science department at IIT Delhi, and an affiliate faculty member at University of Washington, Seattle. His research explores several threads in artificial intelligence, including scaling probabilistic planning algorithms, large-scale information extraction over the Web, and enabling complex computation over crowdsourced platforms. He received his PhD from University of Washington in 2007 and a B.Tech. from IIT Delhi in 2001. He was recently awarded the AAAI Senior Member status for his long-term participation in AAAI and distinction in the field of artificial intelligence.
  • Gabriele Röger: Gabriele Röger is a lecturer at the University of Basel. She received her doctoral degree (Dr. rer. nat) from the University of Freiburg (Germany) in June 2014. Her main research interests are in classical planning with a focus on heuristic search methods. Gabi received the ICAPS Best Dissertation Award in 2016 and was co-author of best papers or best student papers at AAAI (2008, 2015) and ICAPS (2014, 2017).
  • Brian Williams,
  • and Scott Sanner: Scott Sanner is an Assistant Professor in Industrial Engineering and Cross-appointed in Computer Science, both at the University of Toronto. Scott’s research spans a broad range of topics from the data-driven fields of Machine Learning and Information Retrieval to the decision-driven fields of Artificial Intelligence and Operations Research. Scott has applied the analytic and algorithmic tools from these fields to diverse application areas such as recommender systems, interactive text visualization, and Smart Cities applications including transport optimization.

We expect to design a program around a central tread of planning under uncertainty, covering modeling languages, classic and sample-based planning algorithms (such as Monte Carlo Tree Search), reinforcement learning, model-based algorithms in general and heuristic search in particular, as well as several application areas. In difference to previous ICAPS Summer Schools, we plan for the proram to be accomanied by a thread of lab sessions, where school participants will gain practical hands-on experience in the topics covered.


Wednesday 20

Thursday 21

Friday 22

Saturday 23


MDP models, simulator-based algorithms

Reinforcement learning

Model-based algorithms



Welcome / Introduction





Lecture 1:
Introduction to Planning under Uncertainty in MDPs by Scott Sanner.

Lecture 5:
RL by Zico Kolter.

Lecture 9:
Classical planning Heuristics by Malte Helmert and Gabriele Röger.

Lecture 13:
Sequential Optimization for Traffic Signal Control by Scott Sanner.


Coffee break

Coffee break

Coffee break

Coffee break


Lecture 2:
Simulator-based algorithms (basics) by Thomas Keller

Lecture 6:
RL by Zico Kolter.

Lecture 10:
Model-based probabilistic planning by Mausam.

Lecture 14:
CompSust by Iadine Chades.







Lecture 3:
MCTS by Thomas Keller.

Lecture 7:
Classical planning algorithms by Malte Helmert and Gabriele Röger.

Lecture 11:
Model-based probabilistic planning by Mausam.

Lecture 15:
Robotics by Brian Williams.


Coffee break

Coffee break

Coffee break

Final lab session


Lab 1:
Modeling planning problems

Lab 2:
RL algorithms

Lab 3:
Planning algorithms

End 16:30--17:00 (travel to Delft is ca. 20 min bus + 20 min train)

Lecture 1 (Sanner): "Introduction to Planning under Uncertainty in MDPs"

This tutorial provides an introduction to planning under uncertainty based on the framework of Markov Decision Processes (MDPs). After motivating the basic MDP definition, the tutorial will cover a variety of fundamental solution methods that underlie techniques for planning under uncertainty explored in subsequent tutorials.

Lecture 2 (Keller): Introduction to simulation-based algorithms for planning under uncertainty.

We provide an introduction to solution methods for the Multi-Armed Bandit problem and discuss basic sampling algorithms like Hindsight Optimization and Sparse Sampling.

Lecture 3 (Keller): Introduction to Monte-Carlo Tree Search.

We approach the topic by introducing the more general Trial-based Heuristic Tree Search framework, and we discuss action selections ("tree policies"), backup functions, recommendation functions and heuristics ("default policies") that have been used successfully in practice.

Lecture 7 (Helmert & Röger): Classical Planning Algorithms

This tutorial provides an introduction to classical planning. We introduce the mathematical model based on factored state spaces and then describe the three main algorithmic approaches: heuristic search, SAT planning, and symbolic search.

Lecture 9 (Helmert & Röger): Classical Planning Heuristics

This tutorial provides an overview of heuristics for classical planning. We describe the five main concepts underlying heuristics: abstraction, delete relaxation, landmarks, critical paths and network flows. We then present an overview of combination methods and declarative heuristics based on linear programming.

Lecture 13 (Sanner): "Sequential Optimization for Traffic Signal Control"

Urban traffic congestion is a major source of environmental pollution and accounts for billions of dollars of lost productivity worldwide. In this tutorial I will present an overview of traffic flow modeling and novel signal control methods that involve elements of both planning and scheduling.

Application procedure

Applicants must submit the following documents, merged into one PDF and in this order:

  • completed ICAPS Summer School application form
  • a letter describing how the applicant's research topic is connected to the school. This can be light-weight. The purpose of the letter is for the school chairs to be able to confirm, at a high level, that the school content is in principle suited to your background and research.
  • CV
  • a recommendation letter from the applicant's research advisor(s), required only if the applicant is applying for a grant - see below. This is a light-weight letter, that should merely say a few words (< 1/2 page) regarding the student's status, promise, and benefits from the school. It can be either attached or emailed directly to the contact email below.

Applications are submitted through EasyChair (upload the PDF application as a paper with title 'application ', keywords don't matter, you might need to choose three random ones).

The deadline for applications is March 23, 2016.
You can contact in case of questions.

Registration fee and grants

The registration fee is 300 EUR. It covers admission to all school lectures, coffee breaks, and lunch. Accommodation expenses are not included in this fee.

A number of grants will be offered for supporting travel, registration and accommodation. Request for such financial support should be indicated on the application form (see above). Decisions about allocation and size of the grants will be announced on May 11, 2018. Registration fee payment will be due at the registration deadline on May 18, 2018.

Travel directions

Arrival: The closest airport is Amsterdam Airport Schiphol (AMS).

Public transport: The trip from Amsterdam's airport Schiphol to the venue in Noordwijk takes around 1 hour by train and bus, and costs around 10 Euros. A number of connections is available, most typically taking a train for 16 minutes from Schiphol to Leiden, and a Bus for ca. 30 minutes from Leiden to Noordwijk, stop "Pickeplein". The train and bus infrastructure in the Netherlands is extensive, reliable, and easy to plan for using the links below, or Google Maps.

Taxi or cab services: There is a number of companies servicing the airport or available to be called at the hotel reception. Uber is operating in Amsterdam and around the airport; however, their service outside these areas is not always available. Fares from Schiphol to Noordwijk may range from 45 - 90 Euro, or 20-45 Euro from Leiden to Noordwijk.

Connection to ICAPS: The trip to Delft takes just over one hour by public transport, e.g. taking a bus to Leiden (30 min.) and a train from Leiden to Delft (20 min.), and is available every 30 minutes until the late evening.


  • for trips that combine bus and train rides
  • for national train journey information and fares
  • for international train trips
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