Projection in the Epistemic Situation Calculus with Belief Conditionals

Authors: Christoph Schwering, Gerhard Lakemeyer

AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical A fundamental task in reasoning about action and change is projection, which refers to determining what holds after a number of actions have occurred. A powerful method for solving the projection problem is regression, which reduces reasoning about the future to reasoning about the initial state. In particular, regression has played an important role in the situation calculus and its epistemic extensions. Recently, a modal variant of the situation calculus was proposed, which allows an agent to revise its beliefs based on so-called belief conditionals as part of its knowledge base. In this paper, we show how regression can be extended to reduce beliefs about the future to initial beliefs in the presence of belief conditionals. Moreover, we show how any remaining belief operators can be eliminated as well, thus reducing the belief projection problem to ordinary first-order entailments.
Researcher Affiliation Academia Christoph Schwering and Gerhard Lakemeyer Knowledge-Based Systems Group RWTH Aachen University (schwering,gerhard)@kbsg.rwth-aachen.de
Pseudocode No The paper defines a regression operator R with numbered rules (e.g., "R[z, (t1 = t2)] = (t1 = t2)"), but these are presented as definitions within the text, not as a clearly labeled "Pseudocode" or "Algorithm" block.
Open Source Code No The paper does not mention releasing any source code or provide links to a code repository.
Open Datasets No The paper is theoretical and focuses on logical frameworks and proofs. It does not use or reference any datasets for training or evaluation.
Dataset Splits No The paper is theoretical and does not involve empirical validation through dataset splits (train/validation/test) or cross-validation techniques.
Hardware Specification No The paper describes theoretical work and does not mention any hardware specifications used for experiments.
Software Dependencies No The paper describes theoretical work in logic and does not list any specific software dependencies with version numbers.
Experiment Setup No The paper presents a theoretical framework and does not describe any experimental setup details, hyperparameters, or training configurations.