Efficient state-space modularization for planning: theory, behavioral and neural signatures.
Daniel McNameeDaniel M. WolpertMáté LengyelPublished in: NIPS (2016)
Keyphrases
- state space
- heuristic search
- planning problems
- stochastic domains
- network architecture
- neural network
- dynamical systems
- reinforcement learning
- goal state
- data sets
- dynamic programming
- search space
- human behavior
- signature recognition
- macro actions
- markov chain
- decision support
- cost effective
- motion planning
- blocks world