Autonomous Behavior Selection For Self-driving Cars Using Probabilistic Logic Factored Markov Decision Processes
We propose probabilistic logic factored Markov decision processes (PL-fMDPs) as a behavior selection scheme for self-driving cars. Probabilistic logic combines logic programming with probability theory to achieve clear, rule-based knowledge descriptions of multivariate probability distributions, and...
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| Main Authors: | Héctor Avilés, Marco Negrete, Alberto Reyes, Rubén Machucho, Karelly Rivera, Gloria de-la-Garza, Alberto Petrilli |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
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| Series: | Applied Artificial Intelligence |
| Online Access: | https://www.tandfonline.com/doi/10.1080/08839514.2024.2304942 |
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