248 citations · 1.3k across the 45 of their papers we have counts for
8 papers · 1 filter
Learning Perception to Action Rules through Reinforcement Learning for Theory-of-Mind Reasoning
Soyoung Oh, Nursulu Sagimbayeva, Nicholas Jennings +3
In Theory-of-Mind (ToM) reasoning, large language models may correctly infer the agent's mental state but fail to use that inference when predicting or judging the agent's subseque…
The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence
Hector Zenil, Jesper Tegnér, Felipe S. Abrahão +17
Recent advances in machine learning and AI, including Generative AI and LLMs, are disrupting technological innovation, product development, and society as a whole. AI's contributio…
On Population-Based Algorithms for Distributed Constraint Optimization Problems
Saaduddin Mahmud, Md. Mosaddek Khan, Nicholas R. Jennings
Distributed Constraint Optimization Problems (DCOPs) are a widely studied class of optimization problems in which interaction between a set of cooperative agents are modeled as a s…
Time-Sensitive Bayesian Information Aggregation for Crowdsourcing Systems
Matteo Venanzi, John Guiver, Pushmeet Kohli +1
Crowdsourcing systems commonly face the problem of aggregating multiple judgments provided by potentially unreliable workers. In addition, several aspects of the design of efficien…
Efficient Task Collaboration with Execution Uncertainty
Dengji Zhao, Sarvapali D. Ramchurn, Nicholas R. Jennings
We study a general task allocation problem, involving multiple agents that collaboratively accomplish tasks and where agents may fail to successfully complete the tasks assigned to…
Learning Periodic Human Behaviour Models from Sparse Data for Crowdsourcing Aid Delivery in Developing Countries
James McInerney, Alex Rogers, Nicholas R. Jennings
In many developing countries, half the population lives in rural locations, where access to essentials such as school materials, mosquito nets, and medical supplies is restricted.…
Regret-Based Multi-Agent Coordination with Uncertain Task Rewards
Feng Wu, Nicholas R. Jennings
Many multi-agent coordination problems can be represented as DCOPs. Motivated by task allocation in disaster response, we extend standard DCOP models to consider uncertain task rew…
Knapsack based Optimal Policies for Budget-Limited Multi-Armed Bandits
Long Tran-Thanh, Archie Chapman, Alex Rogers +1
In budget-limited multi-armed bandit (MAB) problems, the learner's actions are costly and constrained by a fixed budget. Consequently, an optimal exploitation policy may not be to…