A Probabilistic Extension of Action Language BC+

2018/05/02 by Joohyung Lee, Yi Wang, Lee, Joohyung +1 · 1 citation
Computer Science · #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Logic, Reasoning, and Knowledge #Multi-Agent Systems and Negotiation

paper · pdf · doi:10.48550/arxiv.1805.00634

openalex publication_date 2018/05/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We present a probabilistic extension of action language BC+. Just like BC+ is defined as a high-level notation of answer set programs for describing transition systems, the proposed language, which we call pBC+, is defined as a high-level notation of LPMLN programs---a probabilistic extension of answer set programs. We show how probabilistic reasoning about transition systems, such as prediction, postdiction, and planning problems, as well as probabilistic diagnosis for dynamic domains, can be modeled in pBC+ and computed using an implementation of LPMLN.

Citations

• Probabilistic Reasoning about Actions in Nonmonotonic Causal Theories

Cited by

• iCORPP: Interleaved Commonsense Reasoning and Probabilistic Planning on Robots

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