activity
20162026
most citedThe STRANDS Project: Long-Term Autonomy in Everyday Environments

197 citations · 234 across the 23 of their papers we have counts for

collaborators
Showing cs.AIShow all

7 papers · 1 filter

cs.AI2025

Gaussian Process Aggregation for Root-Parallel Monte Carlo Tree Search with Continuous Actions

Junlin Xiao, Victor-Alexandru Darvariu, Bruno Lacerda +1

Monte Carlo Tree Search is a cornerstone algorithm for online planning, and its root-parallel variant is widely used when wall clock time is limited but best performance is desired…

cs.AI2025

Scalable Solution Methods for Dec-POMDPs with Deterministic Dynamics

Yang You, Alex Schutz, Zhikun Li +3

Many high-level multi-agent planning problems, including multi-robot navigation and path planning, can be effectively modeled using deterministic actions and observations. In this…

cs.AI2024★ 2 cited

Monte Carlo Tree Search with Boltzmann Exploration

Michael Painter, Mohamed Baioumy, Nick Hawes +1

Monte-Carlo Tree Search (MCTS) methods, such as Upper Confidence Bound applied to Trees (UCT), are instrumental to automated planning techniques. However, UCT can be slow to explor…

cs.AI2021

Planning for Risk-Aversion and Expected Value in MDPs

Marc Rigter, Paul Duckworth, Bruno Lacerda +1

Planning in Markov decision processes (MDPs) typically optimises the expected cost. However, optimising the expectation does not consider the risk that for any given run of the MDP…

cs.AI2020

Minimax Regret Optimisation for Robust Planning in Uncertain Markov Decision Processes

Marc Rigter, Bruno Lacerda, Nick Hawes

The parameters for a Markov Decision Process (MDP) often cannot be specified exactly. Uncertain MDPs (UMDPs) capture this model ambiguity by defining sets which the parameters belo…

cs.AI2020★ 1 cited

Convex Hull Monte-Carlo Tree Search

Michael Painter, Bruno Lacerda, Nick Hawes

This work investigates Monte-Carlo planning for agents in stochastic environments, with multiple objectives. We propose the Convex Hull Monte-Carlo Tree-Search (CHMCTS) framework,…

cs.AI2018

Simultaneous Task Allocation and Planning Under Uncertainty

Fatma Faruq, Bruno Lacerda, Nick Hawes +1

We propose novel techniques for task allocation and planning in multi-robot systems operating in uncertain environments. Task allocation is performed simultaneously with planning,…