Fetching the paper…
Reading the bibliography…
When AI systems interact with humans in the loop, they are often called on to provide explanations for their plans and behavior.
A classification of plan modification strategies based on coverage and information requirements
Subbarao Kambhampati · 1990
Earlier work this paper cites.
Trains-95: Towards a mixed-initiative planning assistant
George Ferguson, James F Allen, Bradford W Miller, et al · 1996
Earlier work this paper cites.
Pddl-the planning domain definition language
Drew McDermott, Malik Ghallab, Adele Howe, Craig Knoblock, Ashwin Ram, Manuela Veloso, Daniel Weld, and David Wilkins · 1998
Earlier work this paper cites.
Artificial intelligence: a modern approach
Stuart Jonathan Russell, Peter Norvig, John F Canny, Jitendra M Malik, and Douglas D Edwards · 2003
Earlier work this paper cites.
Mapgen: mixed-initiative planning and scheduling for the mars exploration rover mission
Mitchell Ai-Chang, John Bresina, Len Charest, Adam Chase, JC-J Hsu, Ari Jonsson, Bob Kanefsky, Paul Morris, Kanna Rajan, Jeffrey Yglesias, et al · 2004
Earlier work this paper cites.
Val: Automatic plan validation, continuous effects and mixed initiative planning using pddl
Richard Howey, Derek Long, and Maria Fox · 2004
Earlier work this paper cites.
The fast downward planning system
Malte Helmert · 2006
Earlier work this paper cites.
The structure and function of explanations
Tania Lombrozo · 2006
Earlier work this paper cites.
Monitoring plan optimality during execution
Christian Fritz and Sheila A McIlraith · 2007
Cited alongside, same era.
Representing Excuses in Social Dependence Networks
Guido Boella, Jan Broersen, Leendert van der Torre, and Serena Villata · 2009
Cited alongside, same era.
Coming up with good excuses: What to do when no plan can be found
Moritz Göbelbecker, Thomas Keller, Patrick Eyerich, Michael Brenner, and Bernhard Nebel · 2010
Cited alongside, same era.
Preferred explanations: Theory and generation via planning
Shirin Sohrabi, Jorge A. Baier, and Sheila A. McIlraith · 2011
Cited alongside, same era.
Explanation and abductive inference
Tania Lombrozo · 2012
Cited alongside, same era.
On the revision of planning tasks
Andreas Herzig, Viviane Menezes, Leliane Nunes de Barros, and Renata Wassermann · 2014
Cited alongside, same era.
Pyperplan
Yusra Alkhazraji, Matthias Frorath, Markus Grützner, Thomas Liebetraut, Manuela Ortlieb, Jendrik Seipp, Tobias Springenberg, Philip Stahl, Jan Wülfing, Malte Helmert, and Robert Mattmüller · 2016
Later among the works it cites.
Maintaining evolving domain models
Dan Bryce, J. Benton, and Michael W. Boldt · 2016
Later among the works it cites.
Explicable robot planning as minimizing distance from expected behavior
Anagha Kulkarni, Tathagata Chakraborti, Yantian Zha, Satya Gautam Vadlamudi, Yu Zhang, and Subbarao Kambhampati · 2016
Later among the works it cites.
Explainable agency in human-robot interaction
Pat Langley · 2016
Later among the works it cites.
Dynamic generation and refinement of robot verbalization
Vittorio Perera, Sai P Selveraj, Stephanie Rosenthal, and Manuela Veloso · 2016
Later among the works it cites.
Discovering underlying plans based on distributed representations of actions
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
New algorithms for the top-k planning problem
Anton Riabov, Shirin Sohrabi, and Octavian Udrea · 2014
Cited alongside, same era.
The Ditmarsch Tale of Wonders
Hans van Ditmarsch · 2014
Cited alongside, same era.
Xin Tian, Hankz Hankui Zhuo, and Subbarao Kambhampati · 2016
Later among the works it cites.
Goal recognition design with stochastic agent action outcomes
Christabel Wayllace, Ping Hou, William Yeoh, and Tran Cao Son · 2016
Later among the works it cites.
Plan explicability and predictability for robot task planning
Yu Zhang, Sarath Sreedharan, Anagha Kulkarni, Tathagata Chakraborti, Hankz Hankui Zhuo, and Subbarao Kambhampati · 2017
Closest in time.