Paper-Conference

Towards Topologically Diverse Probabilistic Planning Benchmarks

Markov Decision Processes (MDPs) are often used in Artificial Intelligence to solve probabilistic sequential decision-making problems. …

Jaël Champagne Gareau, Éric Beaudry, Vladimir Makarenkov

Increased Plan Stability in Cooperative Electric Vehicles Path-Planning

The Cooperative Electric Vehicles Planning Problem (CEVPP) has recently been proposed as a multi-agent variant of the Electric Vehicle …

Jaël Champagne Gareau, Guillaume Gosset, Marc-André Lavoie, Éric Beaudry, Vladimir Makarenkov

Cooperative Electric Vehicles Planning

This paper introduces the Cooperative Electric Vehicles Planning Problem (CEVPP), which consists in finding a path for each vehicle of …

Jaël Champagne Gareau, Marc-André Lavoie, Guillaume Gosset, Éric Beaudry

Cache-Efficient Dynamic Programming MDP Solver

Automated planning research often focuses on developing new algorithms to improve the computational performance of planners, but …

Jaël Champagne Gareau, Guillaume Gosset, Éric Beaudry, Vladimir Makarenkov

Cache-Efficient Memory Representation of Markov Decision Processes

Research in automated planning typically focuses on the development of new or improved algorithms. Yet, an equally important but often …

Jaël Champagne Gareau, Éric Beaudry, Vladimir Makarenkov

pcTVI: Parallel MDP Solver Using a Decomposition Into Independent Chains

Markov Decision Processes (MDPs) are useful to solve real-world probabilistic planning problems. However, finding an optimal solution …

Jaël Champagne Gareau, Éric Beaudry, Vladimir Makarenkov

A Fast Electric Vehicle Path-Planner Using Clustering

Over the past few years, several studies have considered the problem of Electric Vehicle Path Planning with intermediate recharge …

Jaël Champagne Gareau, Éric Beaudry, Vladimir Makarenkov

Fast and Optimal Planner for the Discrete Grid-Based Coverage Path-Planning Problem

This paper introduces a new algorithm for solving the discrete grid-based coverage path-planning (CPP) problem. This problem consists …

Jaël Champagne Gareau, Éric Beaudry, Vladimir Makarenkov

An Energy-Efficient Method with Dynamic GPS Sampling Rate for Transport Mode Detection and Trip Reconstruction

This paper presents a novel approach for trip reconstruction and transport mode detection. While traditional methods use a fixed GPS …

Jonathan Milot, Jaël Champagne Gareau, Éric Beaudry

An Efficient Electric Vehicle Path-Planner That Considers the Waiting Time

In the last few years, several studies have considered different variants of the Electric Vehicle Journey Planning (EVJP) problem that …

Jaël Champagne Gareau, Éric Beaudry, Vladimir Makarenkov