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Found 15 papers, 3 papers with code
Solving a Real-World Package Delivery Routing Problem Using Quantum Annealers
Research focused on the conjunction between quantum computing and routing problems has been very prolific in recent years.
A Quantum Computing-based System for Portfolio Optimization using Future Asset Values and Automatic Reduction of the Investment Universe
One of the problems in quantitative finance that has received the most attention is the portfolio optimization problem.
Hybrid classical-quantum computing: are we forgetting the classical part in the binomial?
The expectations arising from the latest achievements in the quantum computing field are causing that researchers coming from classical artificial intelligence to be fascinated by this new paradigm.
Solving Logistic-Oriented Bin Packing Problems Through a Hybrid Quantum-Classical Approach
The Bin Packing Problem is a classic problem with wide industrial applicability.
Benchmark dataset and instance generator for Real-World Three-Dimensional Bin Packing Problems
In this article, a benchmark for real-world bin packing problems is proposed.
Using Offline Data to Speed-up Reinforcement Learning in Procedurally Generated Environments
Motivated by the recent success of Offline RL and Imitation Learning (IL), we conduct a study to investigate whether agents can leverage offline data in the form of trajectories to improve the sample-efficiency in procedurally generated environments.
Hybrid Approach for Solving Real-World Bin Packing Problem Instances Using Quantum Annealers
Efficient packing of items into bins is a common daily task.
Towards Improving Exploration in Self-Imitation Learning using Intrinsic Motivation
Unfortunately, in a broad range of problems the design of a good reward function is not trivial, so in such cases sparse reward signals are instead adopted.
Analyzing the behaviour of D'WAVE quantum annealer: fine-tuning parameterization and tests with restrictive Hamiltonian formulations
Despite being considered as the next frontier in computation, Quantum Computing is still in an early stage of development.
An Evaluation Study of Intrinsic Motivation Techniques applied to Reinforcement Learning over Hard Exploration Environments
In the last few years, the research activity around reinforcement learning tasks formulated over environments with sparse rewards has been especially notable.
Collaborative Training of Heterogeneous Reinforcement Learning Agents in Environments with Sparse Rewards: What and When to Share?
In this work we combine ideas from intrinsic motivation and transfer learning.
Focusing on the Hybrid Quantum Computing -- Tabu Search Algorithm: new results on the Asymmetric Salesman Problem
Quantum Computing is an emerging paradigm which is gathering a lot of popularity in the current scientific and technological community.
Hybrid Quantum Computing -- Tabu Search Algorithm for Partitioning Problems: preliminary study on the Traveling Salesman Problem
Quantum Computing is considered as the next frontier in computing, and it is attracting a lot of attention from the current scientific community.
A Coevolutionary Variable Neighborhood Search Algorithm for Discrete Multitasking (CoVNS): Application to Community Detection over Graphs
The second contribution of this paper is the application field, which is the optimal partitioning of graph instances whose connections among nodes are directed and weighted.
Lights and Shadows in Evolutionary Deep Learning: Taxonomy, Critical Methodological Analysis, Cases of Study, Learned Lessons, Recommendations and Challenges
In summary, three axes - optimization and taxonomy, critical analysis, and challenges - which outline a complete vision of a merger of two technologies drawing up an exciting future for this area of fusion research.
