Peer-Reviewed Papers (In Chronological Order)
- Masataro Asai, Akihiro Kishimoto, Adi Botea, Radu Marinescu, Elizabeth Daly M, and Spyros Kotoulas. 2017. Efficient Optimal Search under Expensive Edge Cost Computation. In IJCAI-2017. pdf
- Asai, M.; Fukunaga, A: 2017. “Exploration Among and Within Plateaus in Greedy Best-First Search”. In ICAPS2017. pdf
- Asai, M.; Fukunaga, A: 2017. “Tie-Breaking Strategies for Cost-Optimal Best First Search.” Journal of Artificial Intelligence Research 58 (2017): 67-121. pdf
- Asai, M.; Fukunaga, A: 2016. Tiebreaking Strategies for A* Search: How to Explore the Final Frontier. In AAAI-2016. pdf presentation poster. (Also submitted to Japanese Society for Artificial Intelligence, received JSAI Annual Conference Student Incentive Award)
- Asai, M.; Fukunaga, A: 2015. Solving Large-Scale Planning Problems by Decomposition and Macro Generation. In ICAPS2015. pdf . CAP planner is available at https://github.com/guicho271828/CAP .
- Asai, M.; Fukunaga, A: 2014. Fully Automated Cyclic Planning for Large-Scale Manufacturing Domains. In ICAPS2014. pdf poster presentation
Presentation can be moved forward/backward with N/P key. For the further help and usage, click here.
- Asai, M.; Fukunaga, A: 2017. Classical Planning in Deep Latent Space: From Unlabeled Images to PDDL (and back). Knowledge Engineering for Planning and Scheduling (KEPS) Workshop (ICAPS2017). An extended manuscript on arxiv
- Asai, M.; Fukunaga, A: 2017. Tie-Breaking in A* as Satisficing Search. Heuristics and Search for Domain-independent Planning (HSDIP) Workshop (ICAPS2017).
- Asai, M.: 2017. Exploiting Search Space Structure in Classical Planning: Analyses and Algorithms (Dissertation Abstract, 2017 version). (ICAPS2017 Doctorial Consortium). pdf
- Asai, M.: 2016. Exploiting Search Space Structure in Classical Planning: Analyses and Algorithms (Dissertation Abstract). (ICAPS2016 Doctorial Consortium). pdf
- Endo, S; Asai, M.; Fukunaga, A: 2014. Evaluation of a Simple, Window-based, Replanning Approach to Plan Optimization. Heuristics and Search for Domain-independent Planning (HSDIP) Workshop (ICAPS2016). pdf presentation
- Asai, M.; Fukunaga, A: 2014. Applying Problem Decomposition to Extremely Large
Planning Domains. Knowledge Engineering for Planning and Scheduling (KEPS) Workshop
(ICAPS2014). pdf (
submitted version–> final version) poster presentation
See my github repo for the latest activity!
- CAP – Component Abstraction Planner, which decompose the given problem,
solve each subproblem, make the subplans into macros and then plans in an
enhanced problem with those macros
- 1.5 coverage in large domains!
- Higer coverage in ipc2011 learning track, without learning time!
- PDDL – A Common Lisp library to read/write/analyse PDDL files. It has
- a PDDL reader / parser
- CLOS-based object oriented interface to analyse each objects
- various useful accessors for objects e.g. predicate/propositions/action/types
- methods like
(ground-action action objects)
- a pretty formatter
- a simulator (STRIPS and action-costs are supported)
- CELL-ASSEMBLY – The PDDL files and the explanation of a CELL-ASSEMBLY
manufacturing domain, which appears at [Asai, Fukunaga ICAPS2014]
- Is currently enlisted as one of “Real and Realistic Planning Domains” by Patrik Haslum
- aaai-template – For org-mode lovers and reserchers of artificial intelligence. A
set of scripts and templates for faster publishing of papers with AAAI
- converting SVG images to grayscale pngs (I recommend Inkscape as an editor)
- typeset the TeX files with pdflatex
- checks for any Overfull hbox
- checks for paper limit
- Combination of simple scripts
make-periodicallywould be useful. It waits for the changes, and if a change is detected, it runs
make, then notify the result via
inotify(pop up inteface available in gtk).