Name
Abstract | ||
|---|---|---|
This paper presents a robotic behavior planning method under uncertainty based on biology-inspired episodic memory. Adaptive behavior planning, prediction and reasoning are achieved between tasks, environment, and threats. Through building a novel episode model and introducing the activation and stimulation mechanism of state neurons, the framework of an episodic memory-driving Markov decision pro... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TIE.2016.2613507 | IEEE Transactions on Industrial Electronics |
Keywords | Field | DocType |
Neurons,Planning,Uncertainty,Robot sensing systems,Computational modeling | Episodic memory,Computer science,Markov decision process,Aliasing,Artificial intelligence,Behavior-based robotics,Robot,Cognition,Adaptive behavior,Machine learning,Computational complexity theory | Journal |
Volume | Issue | ISSN |
64 | 2 | 0278-0046 |
Citations | PageRank | References |
2 | 0.36 | 22 |
Authors | ||
3 | ||