5 papers
Reinforcement Learning for Sequential Solar PV Policy Design under Uncertainty: An Agent-Based Approach
Iias Faiud, Jonaid Shianifar, Michael Schukat +1
Designing effective and fiscally sustainable policies for solar photovoltaic (PV) adoption requires balancing adoption gains against public expenditure under uncertainty and hetero…
LLM-Assisted Behavioural and Scenario Augmentation for Agent-Based Energy Adoption Models
Iias Faiud, Hossein Khaleghy, Michael Schukat +1
Recent advances in large language models (LLMs) create opportunities to enrich simulation-based energy policy analysis, particularly by supporting structured behavioural assumption…
AI World Cup 2026: Benchmarking Large Language Models for End-to-End Football Tournament Prediction
Jonaid Shianifar, Iias Faiud
Large language models (LLMs) are now regularly asked to forecast real-world events, but comparisons are often difficult because models receive different information, use different…
Modelling Solar PV Adoption in Irish Dairy Farms using Agent-Based Modelling
Iias Faiud, Michael Schukat, Karl Mason
The agricultural sector is facing mounting demands to enhance energy efficiency within farm enterprises, concurrent with a steady escalation in electricity costs. This paper focuse…
Integrating Renewable Energy in Agriculture: A Deep Reinforcement Learning-based Approach
A. Wahid, I faiud, K. Mason
This article investigates the use of Deep Q-Networks (DQNs) to optimize decision-making for photovoltaic (PV) systems installations in the agriculture sector. The study develops a…