If you are a DC student, please spend a few minutes to go through this opinion survey.
New! The doctoral consortium proceedings are now online (3.82MB).
The DC program consists of two events:
A) DC meeting on September 19th (whole day). This meeting comprises short oral presentations, activities in themed-cluster working groups and meetings with mentors. More particularly, the schedule for this day is:
09:00-09:30 | Introduction amphitheater 9 |
09:30-10:30 | Themed-cluster
working groups. Each student will have 15 minutes for
oral presentation. amphitheaters 9, 8, 7, 5 and 4 for clusters 1, 2, 3, 4 and 5 respectively |
10:30-11:00 | Coffee break |
11:00-12:30 | Themed-cluster
working groups - mentoring activity amphitheaters 9, 8, 7, 5 and 4 for clusters 1, 2, 3, 4 and 5 respectively |
12:30-14:00 | Lunch break |
14:00-14:30 | Invited talk by Subbarao Kambhampati:
How to write a research paper (and not to die trying it). amphitheater 9 |
14:30-15:30 | Themed-cluster
working groups. Preparation of a roadmap for the final
global debriefing amphitheaters 9, 8, 7, 5 and 4 for clusters 1, 2, 3, 4 and 5 respectively |
15:30-16:00 | Coffee break |
16:00-17:30 |
Final global debriefing (all DC students). Each working
group will have 15 minutes for oral presentation |
17:30-18:00 | Conclusions amphitheater 9 |
There will be five clusters, organised as follows:
Student |
Paper |
|
Andrey Kolobov |
Integrating Paradigms for Approximate Probabilistic Planning |
Daniel Bryce |
Marcello Cirillo |
A Human-Aware Robot Task Planner |
Daniel Bryce |
Omar Zia Khan |
Minimal Sufficient Explanations for Factored Markov Decision
Processes |
|
Student |
Paper |
|
Masahiro Ono |
Market-based Risk Allocation for Multi-agent Systems |
Federico Pecora |
Frederik Heger |
A Hybrid Assembly Task Planning System: Where Motion
Planning Helps Symbolic Planning Find Good Solutions For
Real-World Applications |
Federico Pecora |
Kartik Talamadupula |
Integrating a Closed World Planner and an Open World Robot |
Ari Jonsson |
Alexander Niveau |
Using Interval Automata to Represent Decision Policies with
Continuous Variables |
Ari Jonsson |
Student |
Paper |
|
Xiaoxun Sun |
Efficient Incremental Search for Moving Target Search |
Adi Botea |
Jordan Thayer |
Revisiting Bounded Suboptimal Heuristic Search |
Adi Botea |
Hootan Nakhost |
Action Elimination and Plan Neighborhood Graph Search: Two
Algorithms for Plan Improvement |
Joerg Hoffmann |
Erez Karpas |
Learning to Combine Admissible Heuristics Under Bounded Time |
Derel Long |
Student |
Paper |
|
Nir Lipovetzky |
Inference and Decomposition in Planning Using Causal
Consistent Chains |
T. Lee McCluskey |
Alan Lindsay |
Learning Policies to Exploit an Extended Domain Model |
Daniel Borrajo |
James MacGlashan |
Hierarchical Skill Learning for High-Level Planning |
Susana Fernández |
Shahin Shah |
An Investigation into Using Object Constraints to Synthesize
Planning Domain Models |
Daniel Borrajo |
Student |
Paper |
|
Robert Effinger |
Dynamic Controllability of Temporally-flexible Reactive
Programs |
Andrew Coles |
Mauro Vallati |
An Automatically Configurable Portfolio-based Planner with
Macro-actions: PbP |
Andrew Coles |
Patrick Conrad |
Flexible Execution of Plans with Choice |
Angelo Oddi |
Melissa Liew |
Issues in Temporal Planning using Timed Petri Nets |
Angelo Oddi |
Antonio Garrido, Universitat Politècnica de València, Spain
Eva Onaindia, Universitat Politècnica de València, Spain