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1Compressed Conditional Mean Embeddings for Model-Based Reinforcement Learning
G. Lever, J. Shawe-Taylor, R. Stafford, and {. Szepesvári. AAAI-2016, page 1779--1787. (November 2016)
5 years ago by @csaba
show all tags
approximation,
Markov
pseudo-MDPs
model-based
abstraction,
Decision
control
planning,
Processes,function
RL,
learning,
reinforcement
control,
approximation,Markovpseudo-MDPsmodel-basedabstraction,Decisioncontrolplanning,Processes,functionRL,learning,reinforcementcontrol,
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1Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstractions
A. Isaza, {. Szepesvári, V. Bulitko, and R. Greiner. UAI, page 306--314. (2008)
5 years ago by @csaba
show all tags
path
learning,
macro
abstraction,
finite
problem,
options
MDPs,
shortest
planning,
pathlearning,macroabstraction,finiteproblem,optionsMDPs,shortestplanning,
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1Load Estimation for Microgrid Planning Based on a Self-Organizing Map Methodology
J. Llanos, R. Morales, A. Nunez, D. Saez, M. Lacalle, L. Marin, R. Hernandez, and F. Lanasa. Applied Soft Computing, (2017)
5 years ago by @dqcauchile
show all tags
self-organizing
(som),
dqcauchile
profile
load
map
microgrid,
planning,
self-organizing(som),dqcauchileprofileloadmapmicrogrid,planning,
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1Combining resource selection functions and home-range data to identify habitat conservation priorities for brown bears
M. Pop, R. Iosif, I. Miu, L. Rozylowicz, and V. Popescu. Animal Conservation, 21 (4): 352-362 (2018)
6 years ago by @rozylowicz
show all tags
habitat
bear,
large
coexistence
resource
Carpathians,
carnivores,
selection,
arctos,
myown,
planning,
brown
Ursus
human-wildlife
conservation
connectivity,
habitatbear,largecoexistenceresourceCarpathians,carnivores,selection,arctos,myown,planning,brownUrsushuman-wildlifeconservationconnectivity,
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1Integrating Planning and Execution in Stochastic Domains
R. Dearden, and R. Boutilier. UAI-94, page 162--169. Seattle, WA, (1994)
8 years ago by @machinelearning
show all tags
MDPs
ml
planning,
MDPsmlplanning,
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1Using Abstractions for Decision-Theoretic Planning with Time Constraints
R. Boutilier, and R. Dearden. Proc.\ 12th National Conference on Artificial Intelligence, page 1016--1022. Seattle, WA, (1994)
8 years ago by @machinelearning
show all tags
MDPs
ml
planning,
MDPsmlplanning,
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2Abstraction and Approximate Decision Theoretic Planning
R. Dearden, and C. Boutilier. Artificial Intelligence, 89 (1): 219--283 (1997)
8 years ago by @machinelearning
show all tags
MDPs
ml
planning,
MDPsmlplanning,
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3Planning with prioritized goals
R. Feldmann, G. Brewka, and S. Wenzel. Proceedings of the Tenth International Conference on Principles of Knowledge Representation and Reasoning (KR 2006), page 503--514. (2006)
14 years ago by @baisemain
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preference
planning,
preferenceplanning,
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1Planning for the sustainability of community-based health programs: conceptual frameworks and future directions for research, practice and policy
M. Shediac-Rizkallah, and L. Bone. Health Education Research, 13 (1): 87--108 (March 1998)PMID: 10178339.
14 years ago by @jelias
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Health
Research,
Policy,
United
Implementation,
Plan
Innovation,
Humans,
Services
Services,
States
Consumer
Organizational
Participation,
Planning,
Community
HealthResearch,Policy,UnitedImplementation,PlanInnovation,Humans,ServicesServices,StatesConsumerOrganizationalParticipation,Planning,Community
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1An Approach for Strategic Planning of Future Technology Portfolios
M. Kirby. (2006)
15 years ago by @atlpwners
show all tags
Calculator
Strategic
Planning,
CalculatorStrategicPlanning,
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1Convention in joint activity
R. Alterman, and A. Garland. Cognitive Science, 25 ((c) 2002 Inst. For Sci. Info): 611-657+ (2001)
16 years ago by @clachapelle
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file-import-09-02-13,
situativity-theory
planning,
file-import-09-02-13,situativity-theoryplanning,
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1Design and technology productions among middle school students: an Indian experience
R. Khunyakari, S. Mehrotra, S. Chunawala, and C. Natarajan. International Journal of Technology and Design Education, 17 (1): 5-22+ (January 2007)
16 years ago by @clachapelle
show all tags
file-import-09-02-13,
collaboration
technology-education
cognition,
drawing,
middle-school,
planning,
designing,
file-import-09-02-13,collaborationtechnology-educationcognition,drawing,middle-school,planning,designing,
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1Soft computing paradigms for hybrid fuzzy controllers: experiments and applications
M. Akbarzadeh-T., E. Tunstel, K. Kumbla, and M. Jamshidi. Proceedings of the 1998 IEEE World Congress on Computational Intelligence, 2, page 1200--1205. Anchorage, Alaska, USA, IEEE Press, (5-9 May 1998)
17 years ago by @brazovayeye
show all tags
algorithm-fuzzy
genetic
behavior-based
mobile
task
intelligence,
hybrid
flexible
networks,
machine
added
DC
drive
controller,
motor,
neural
ability,
controllers,
brushless
direct
learning
motors,
robots,
paradigms,
adaptation,
planning,
systems,
path
link,
algorithms,
programming-fuzzy
robot
manipulators,
computing
navigation
neurocontrollers,
hierarchical
programming,
schemes,
control,
soft
programs,
fuzzy
logic-based
algorithm-fuzzygeneticbehavior-basedmobiletaskintelligence,hybridflexiblenetworks,machineaddedDCdrivecontroller,motor,neuralability,controllers,brushlessdirectlearningmotors,robots,paradigms,adaptation,planning,systems,pathlink,algorithms,programming-fuzzyrobotmanipulators,computingnavigationneurocontrollers,hierarchicalprogramming,schemes,control,softprograms,fuzzylogic-based
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1A Planner for the Automation of Programming Environment Tasks
R. Bisiani, F. Lecouat, and V. Ambriola. Proceedings of the 21st International Hawai Conference on System Sciences, (1988)
18 years ago by @charoy
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agora
planning,
agoraplanning,
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publications (hide)14
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