ALLEGRO: Belief-Based Programming in Stochastic Dynamical Domains
Authors: Vaishak Belle, Hector Levesque
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | It is fully implemented and experiments demonstrate that ALLEGRO could be the basis for bridging high-level programming and probabilistic robotics technologies in a general way. Empirical evaluations are then discussed that demonstrate the promise of the system. |
| Researcher Affiliation | Academia | Vaishak Belle Dept. of Computer Science KU Leuven Belgium vaishak@cs.kuleuven.be Hector J. Levesque Dept. of Computer Science University of Toronto Canada hector@cs.toronto.edu |
| Pseudocode | Yes | We now present pseudo-code for the interpreter of allegro and argue for its correctness relative to the specification above. The interpreter is based on sampling [Murphy, 2012], and its correctness is defined using limits. The overall system is described using three definitions: an evaluator of expressions eval, an epistemic state e, and an interpreter of programs int. |
| Open Source Code | No | The paper does not provide any links to open-source code or explicitly state that the code will be made publicly available. |
| Open Datasets | No | The paper describes a domain model for a robot (Figure 2) but does not use or provide access to a public or open dataset in the context of training or evaluation. |
| Dataset Splits | No | The paper discusses 'sample size' for the epistemic state in the interpreter but does not mention specific train/validation/test dataset splits for experimental reproduction. |
| Hardware Specification | Yes | Experiments were run on Mac OS X 10.9 using a system with 1.4 GHz Intel Core 2 Duo processor, 2 GB RAM, and racket v6.1. |
| Software Dependencies | Yes | Experiments were run on Mac OS X 10.9 using a system with 1.4 GHz Intel Core 2 Duo processor, 2 GB RAM, and racket v6.1. |
| Experiment Setup | Yes | We set the sample size |e0| = 100000. Experiments were run on Mac OS X 10.9 using a system with 1.4 GHz Intel Core 2 Duo processor, 2 GB RAM, and racket v6.1. |