Towards Improving Solution Dominance with Incomparability Conditions: A case-study using Generator Itemset Mining

2019-10-01 · Gökberk Koçak, Özgür Akgün, Tias Guns, Ian Miguel

Finding interesting patterns is a challenging task in data mining. Constraint based mining is a well-known approach to this, and one for which constraint programming has been shown to be a well-suited and generic framework. Dominance programming has been proposed as an extension that can capture an even wider class of constraint-based mining problems, by allowing to compare relations between patterns. In this paper, in addition to specifying a dominance relation, we introduce the ability to specify an incomparability condition. Using these two concepts we devise a generic framework that can do a batch-wise search that avoids checking incomparable solutions. We extend the ESSENCE language and underlying modelling pipeline to support this. We use generator itemset mining problem as a test case and give a declarative specification for that. We also present preliminary experimental results on this specific problem class with a CP solver backend to show that using the incomparability condition during search can improve the efficiency of dominance programming and reduces the need for post-processing to filter dominated solutions.

📄 PDF Abstract BibTeX arXiv:1910.00505

Code (1)

stacs-cp/ModRef2019-Dominance 공식 구현

Methods 이 논문이 사용한 방법론

Test 설명 없음

The Computational Complexity of Dominance and Consistency in CP-Nets

2014-01-15 · Judy Goldsmith, Jerome Lang, Miroslaw Truszczyski, Nic Wilson

We investigate the computational complexity of testing dominance and consistency in CP-nets. Previously, the complexity of dominance has been determined for restricted classes in which the dependency graph of the CP-net …

Mechanism Design with Sequential-Move Games: Revelation Principle

2024-02-21 · Siyang Xiong

Traditionally, mechanism design focuses on simultaneous-move games (e.g., Myerson (1981)). In this paper, we study mechanism design with sequential-move games, and provide two results on revelation principles for general…

Expected Scalarised Returns Dominance: A New Solution Concept for Multi-Objective Decision Making

2021-06-02 · Conor F. Hayes, Timothy Verstraeten, Diederik M. Roijers, Enda Howley 외

In many real-world scenarios, the utility of a user is derived from the single execution of a policy. In this case, to apply multi-objective reinforcement learning, the expected utility of the returns must be optimised. …

Decision Making Multi-Objective Reinforcement Learning reinforcement-learning Reinforcement Learning+1

Multiagent Reinforcement Learning in Games with an Iterated Dominance Solution

2019-09-25 · Yoram Bachrach, Tor Lattimore, Marta Garnelo, Julien Perolat 외

Multiagent reinforcement learning (MARL) attempts to optimize policies of intelligent agents interacting in the same environment. However, it may fail to converge to a Nash equilibrium in some games. We study independen…

reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Uncertainty-Encoded Multi-Modal Fusion for Robust Object Detection in Autonomous Driving

2023-07-30 · Yang Lou, Qun Song, Qian Xu, Rui Tan 외

Multi-modal fusion has shown initial promising results for object detection of autonomous driving perception. However, many existing fusion schemes do not consider the quality of each fusion input and may suffer from adv…

Autonomous Driving Mixture-of-Experts Object object-detection+2