Bridging Commonsense Reasoning and Probabilistic Planning via a Probabilistic Action Language

DOI10.1017/S1471068419000371zbMath1434.68551arXiv1907.13482OpenAlexW2974390546MaRDI QIDQ5108524

Joohyung Lee, Yi Wang, Shiqi Zhang

Publication date: 4 May 2020

Published in: Theory and Practice of Logic Programming (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1907.13482

zbMATH Keywords

commonsense reasoningprobabilistic logic programmingPOMDPprobabilistic planningaction language

Mathematics Subject Classification ID

Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20) Logic programming (68N17)

Related Items (1)

Statistical relational extension of answer set programming

Uses Software

• CCalc
• REBA
• PEORL

Cites Work

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• Planning and acting in partially observable stochastic domains
• A synthesis of automated planning and reinforcement learning for efficient, robust decision-making
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• Elaboration tolerant representation of Markov decision process via decision-theoretic extension of probabilistic action language \(p\mathcal{BC}+\)
• Robot task planning and explanation in open and uncertain worlds
• Online Action Language $$o\mathcal {BC}$$+
• Probabilistic reasoning with answer sets
• A Probabilistic Extension of Action Language
• Computing LP^MLN using ASP and MLN solvers
• REBA: A Refinement-Based Architecture for Knowledge Representation and Reasoning in Robotics

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