Multi-Context System for Optimization Problems
Authors: Tiep Le, Tran Cao Son, Enrico Pontelli2929-2937
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | This paper proposes Multi-context System for Optimization Problems (MCS-OP) by introducing conditional costassignment bridge rules to Multi-context Systems (MCS). This novel feature facilitates the deļ¬nition of a preorder among equilibria, based on the total incurred cost of applied bridge rules. As an application of MCS-OP, the paper describes how MCS-OP can be used in modeling Distributed Constraint Optimization Problems (DCOP), a prominent class of distributed optimization problems that is frequently employed in multi-agent system (MAS) research. The paper shows, by means of an example, that MCS-OP is more expressive than DCOP, and hence, could potentially be useful in modeling distributed optimization problems which cannot be easily dealt with using DCOPs. It also contains a complexity analysis of MCS-OP. |
| Researcher Affiliation | Academia | Tiep Le, Tran Cao Son, Enrico Pontelli Department of Computer Science New Mexico State University {tile, tson, epontell}@cs.nmsu.edu |
| Pseudocode | No | The paper describes concepts and provides formal definitions and examples, but it does not include any pseudocode blocks or algorithms. |
| Open Source Code | No | The paper does not provide any link to source code for the methodology. It mentions a supplemental file URL, but specifies it is for "most proofs of lemmae and theorems". |
| Open Datasets | No | The paper is theoretical and uses examples to illustrate the proposed framework. It does not involve any datasets, public or otherwise, for training, validation, or testing. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical validation with dataset splits. It relies on formal definitions, theorems, and illustrative examples. |
| Hardware Specification | No | The paper is theoretical and describes a new framework. It does not mention any specific hardware used for computations or experiments. |
| Software Dependencies | No | The paper mentions logical frameworks like Answer Set Programming (ASP) and Propositional Logic (PL) and general "ASP solvers," but does not specify any particular software names with version numbers that would be necessary to replicate any computational aspects described. |
| Experiment Setup | No | The paper proposes a theoretical framework and uses examples to illustrate its concepts and expressivity. It does not describe an experimental setup with specific hyperparameters, training configurations, or other system-level settings typically found in empirical research. |